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- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
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Untangle Solving problems with fuzzy constraints Untangle Solving problems
with fuzzy constraints Szymon Kaliski Marcel Goethals Mike Kluev January
2023 Have you ever needed to find a time for all your friends to meet for
dinner or to create a seating plan for wedding guests These are examples
of problems that require navigating a set of overlapping constraints you
are only available on every other Tuesday or Thursday Chris will not show
up if Ash is not there but Ash is in town only the last week of November
and you really wanted to catch up with Chris We often work out problems
like this with a pencil and paper experimenting until we find a solution
but it feels like computers should be the perfect tool to help us In fact
there are programming tools called theorem provers which are designed to
solve exactly this class of problems They excel at helping experts work
through fullyspecified problems with a clear solution Unfortunately we
rarely have a formal understanding of our problems We come to understand
them interactively by trying to find a solution In fact we often just need
a solution that is good enough instead of one proven to be optimal We set
out to experiment with interactive computerassistance for this type of
thinking Untangle is a research prototype that helps you think through
everyday constraint problems using your tablet stylus With Untangle you
leave handdrawn marks on a page sketch out the representation of your
problem introduce constraints graphically and browse through sets of
possible solutions This work was presented as a part of our Programmable
Ink talk at Strange Loop 2022 We welcome your feedback inkandswitch or
helloinkandswitchcom Contents Thinking fuzziness and constraints Design
principles Inspirations Logic programming Pattern matching Graphical
production systems Realworld applications of logic programming Untangle
Assignment problem Frequency assignment bids Coffee shop schedule
Generative art Recursive rewrites Findings A smooth ramp from concrete to
abstract helps form intuitions about the system Informal solving is most
useful for certain kinds of problems Many problem representations look
like tables Handdrawn input is well aligned with exploratory
problemsolving Fuzziness and live feedback contribute to a conversational
feel Shortcomings The system lacks clear semantics Turning ink into
symbols is an unnecessary technical crutch Some parts of the system lack
visibility Responses from the computer are underdesigned Small canvas
artificially constrains the problem representation There is no way to
explore the solution space Conclusions Thinking fuzziness and constraints
Computers can be great at solving logic problems like the ones mentioned
above as long as we can describe them in a formally correct and detailed
way Special programming languages and techniques—theorem provers—exist and
can calculate solutions for huge datasets These languages are most often
used by mathematicians to help with proving formal theorems or by domain
experts to aid in modeling large scale industrial production systems A
Constraint satisfaction problem can be solved using logic programming
techniques such as Satisfiability Modulo Theories SMT or Answer Set
Programming ASP These programming languages are useful after we have
encoded a problem in machinereadable form but first we must do the harder
part fully understand the problem For this we often reach for pen and
paper which allows us to think fuzzily and omit various levels of detail
when problemsolving We can quickly sketch out the representation of the
problem without worrying about absolute correctness For a sampling of
realworld pen paper constraint problem representations have a look at How
People Visually Represent Discrete Constraint Problems by Xu Zhu et al
This project explores what it might look like if computers could support
this style of earlystage thinking Untangle is specifically not a tool for
solving artificial logic puzzles nor is it a tool for creating formal
specifications for industrial systems Instead we are interested in a tool
that can help us think through illdefined problems understand compromises
and learn about what kind of questions to ask Untangle is a continuation
of the threads highlighted in the thinking modeling and computers section
of the Crosscut essay Mainly we want a tool in which we can sketch a
dynamic representation of the problem at hand and have a conversation with
it Design principles Keep focus on the problem not the implementationWe
want a tool in which your focus remains on the problem at hand as much as
possible rather than thinking about the correct way to encode it in a
machinereadable way No errors undefined values or unknown parameters to
fill inThe tool should never block freeze or become unresponsive even if
the user creates invalid states such as errors or incomplete input A wrong
answer is better than no answer Everything is visibleBoth the domain model
and the constraints should always be visible and interactive Conversation
with the material is be encouragedWe want an iterative approach to problem
solving—one where observing leads to thinking which leads to acting which
leads back to observing You should be able to intuit connections between
various rules and constraints by wiggling them and seeing other things
wobble We also adopted most of the design principles from Crosscut A
tablet stylus can become dynamic pen paper The content of what you are
working on is the most important thing You should not have to use an
onscreen keyboard for programming This is a personal thinking space
Untangle shares a lot of context with Crosscut a research project in which
we explored an approach to building dynamic models by direct manipulation
There is one important design difference from Crosscut using handdrawn
strokes instead of vector graphics We believe there is something special
about leaving distinctively human marks on the page with a stylus so we
want to go back to handdrawn marks like with Inkbase but with an entirely
different computational model Inspirations Logic programming Logic
programming is an important paradigm in computer science It is based on
formal logic and allows programmers to describe problems using declarative
statements “every human is mortal” and ask questions based on these
statements “X is human is X mortal” Some notable logic programming
languages include Prolog one of the first logic programming languages
widely used for theorem proving term rewriting automated planning Z3
Theorem Prover a satisfiability modulo theories SMT solver that is
targeted at software verification and program analysis Untangle uses Z3 as
a library for solving Alloy Analyzer Alloy is a language for describing
and exploring software models It has been used in a wide range of
applications from finding holes in security mechanisms to designing
telephone switching networks Of particular interest is Alloy’s IDE that
visualizes a possible structure based on the constraints provided by the
user Alloy Analyzer’s interactive solver visualization Pattern matching
Untangle relies heavily on spatial queries—finding symbols on the page by
their spatial relation to other known symbols—which were inspired by Regex
a domainspecific language for describing search patterns in text
Qualitative Spatial Reasoning a calculus which allows a machine to
represent and reason about spatial entities without resorting to
traditional quantitative techniques QSR is often used in GIS Geographic
Information Systems for querying geographical data For more information on
QSR check out A survey of qualitative spatial representations by Chen et
al Graphical production systems Work on Untangle was also inspired by
graphical production systems which use shape matching rules and graphical
rewrites to describe computations Publications that guided our work Shape
Grammars and the Generative Specification of Painting and Sculpture a
seminal paper by Stiny and Gips introducing shape grammars New graphical
reasoning models for understanding graphical interfaces a paper from
Furnas introducing BICPICT a pixelrewriting graphical reasoning system
Wave Function Collapse an approach for generating tile maps from a single
example which influenced our thinking on using superposition as a mental
model for working with multiple possible values Wave Function Collapse
algorithm visualzation Figure by Maxim Gumin Realworld applications of
logic programming Finally we were guided by various examples of using
theorem provers for working through everyday problems How people visually
represent discrete constraint problems Using linear programming GLPK for
scheduling problems Tax planning with Z3 Theorem Prover A shared pinboard
becomes a collaborative modeling tool to plan a dinner party Untangle We
are now going to introduce Untangle a tool for working out realworld logic
problems Assignment problem To explore the basic concepts of the tool we
are going to look at an assignment problem imagine you are teaching a
class it is the end of the semester and each student needs to submit a
short paper about some topic You want students to grade each other so you
have less work to do Let us see how Untangle can help us solve this
problem This reallife problem comes from Joshua Horowitz thank you Josh In
its most basic form Untangle allows you to automatically assign symbols to
other symbols For example you can put Bob into a box by drawing an arrow
between the text Bob and the box—Bob will now appear in pink inside the
box A symbol is anything that appears on the canvas Symbols can be a
single stroke or collections of strokes Assigning Bob to a box We can also
assign multiple symbols to a box Untangle will now show that there are two
possible assignments by showing two dots at the bottom of the screen We
can scroll through the different solutions Bob and Eve Assigning multiple
students to the same box There are six students in our class so we will
write all of their names Instead of drawing six arrows we can use spatial
queries to find elements on the canvas Using a spatial query to grab all
of the student names Whenever we make a selection of symbols on the canvas
a popup appears This popup suggests different spatial queries we can use
to match our selection In this case it suggests that we could look for a
vertical column of symbols starting with Bob Representation of a spatial
query capturing a column of symbols starting with Bob We can place this
query onto the canvas and use it as a shortcut to refer to all the symbols
that match it The matching symbols are highlighted in the same color for
additional visual feedback Untangle only ever places one symbol into each
box Whenever there are multiple ways to assign symbols Untangle will
generate multiple solutions but display only one The dots at the bottom of
the screen indicate that there are alternative possible assignments We can
get a sense of the different solutions by scrolling through them Solution
switcher We want to assign a student to every other student so let us
create an empty box next to every name Just like with the spatial query
for a list of names we can create a query that simply looks for all boxes
This generates all possible ways to assign one student to another one
Using the all boxes query to assign every student to another student
Currently students are sometimes assigned to grade themselves While
students will surely be happy to do so as a teacher I would rather avoid
this situation Let us add a rule that prevents students from grading
themselves To do this we will add a third spatial query This query matches
any box that has something to the left of it The question mark acts as a
wildcard matching any symbol Using wildcard to capture something next to a
box and make that something not equal to the contents of the box Finally
we can draw an inequality constraint arrow This expresses that whatever
ends up in the box cannot be the same as whatever symbol is on its left
Bob can no longer grade Bob Inequality constraint Let us say we omitted a
student when writing the original list of names Because we are using
spatial queries to describe the column of student names we can easily
extend the list Extending the student list with a new name The results
update reactively It turns out that Bob and Claire have written papers
about similar topics So it would be great if they grade each other We can
ensure this by simply putting their names into the corresponding boxes and
the system will adapt accordingly Forcing the assignment of Bob to Claire
Again the system reacts with new results Frequency assignment bids To show
a few more interesting properties of Untangle let us look at a different
example—running frequency spectrum assignment bids The basic idea is that
a specific radio frequency spectrum say 5G is divided into smaller parts
and sold to various operators This reallife problem comes from William
Taysom thank you William Let us start by modeling this problem There are
three telephone companies telcos that are bidding on the frequency
spectrum from 34 GHz to 42 GHz The spectrum is split into eight bands and
the telcos can bid on individual bands Initial model of the spectrum
assignment problem Just as in the student grading example we could use
spatial queries to assign telcos randomly to bands in the spectrum
Assigning operators to random bands of the available spectrum But this is
not really how an auction works Instead telcos bid on a specific number of
bands that they want to obtain For example Verizon might place a bid for
four bands We can model this using a count modifier which limits the
number of times a certain rule applies Using a count modifier to limit the
assignment to four times Let us rearrange the canvas a bit and add some
imaginary bids for each of the companies Modeling bids from all of the
operators Some bands can be more valuable for example the middle bands
often have less interference so a company may bit not just on a specific
number of bands but also specific placement inside the spectrum To model
this we can either draw an arrow directly to the specified band or simply
drag a symbol in place We can guide the solver into a direction that we
care about and it will respond immediately Constraining the solutionspace
further by modeling bids on specific bands in the available spectrum The
number of bids might not equal the number of available slots—an
overconstrained system Using most solvers the result would be an error
message that the constraints are unsatisfiable Instead of showing an error
Untangle will attempt to generate a partially correct solution by ignoring
some of the rules Arrows will turn red indicating that for the currently
shown solution this rule is ignored Relaxing the overconstrained problem
representation by ignoring some of the rules When having a conversation
with the material hearing “no but what if…” is more encouraging than
hearing just “no” The machine does not brake or scold at you for making a
mistake but instead shows compromises and possible directions which in
turn helps generate new ideas Finally companies sometimes bid specifically
on a set of consecutive bands—rather than just bidding on four bands they
want four bands in a row We can model this using a combination of spatial
queries and counts Creating an assignment rule of four consecutive bands
using a combination of spatial queries and count modifiers Coffee shop
schedule In the following example we will show how to create a work
schedule for a coffee shop An easy solution is to assign employees to
random days but to make a good schedule everyone is happy with we need to
consider employee availability To solve this problem we need to two
dimensions First we list availability of the employees in the topleft
corner For each day that an employee is available we draw an X For example
Jim is available on Monday Wednesday and Friday In the bottom right we
draw a simple empty schedule for the week Modeling the baristas
availability Untangle has a special lookup spatial query that allows us to
look up information in tablelike layouts In this case it matches columnrow
pairs together whenever it finds an X Using the lookup spatial query on
the availability table You can think of this as finding all the available
people for each day Untangle will only generate solutions where the day
and name are matched in the availability table Visualization of running
the lookup spatial query We then create a spatial query to find all of the
empty slots in the schedule using a something on left box on right query
Spatial query using a wildcard symbol and a box to the right of it We only
want to assign employees to days they are actually available To do this we
bind the wildcard matches on days of the week We then use the names to
fill in the boxes in the schedules Untangle will show us all possible
schedules based employee availability Resulting coffee shop work schedules
based on employee availability The proposed schedules often have people
working two days in a row—something we might like to avoid We can set up a
simple constraint to make sure no two boxes in a row hold the same value
Constraining consecutive not to hold the same value It is worth noting
that in this example technically all the information needed to solve the
problem is already on the canvas However coming up with a valid solution
still requires serious “System 2” level thinking shuffling around symbols
in your head It feels great to have the system do this part for you System
1 System 2 is a dichotomy introduced by Daniel Kahneman in Thinking Fast
and Slow System 1 describes fast intuitive loweffort thinking while System
2 is effortful and slow Generative art So far all the examples we looked
at were about constraining the solution space—progressively going towards
a small set of satisfying solutions This is only a one part of the
problemsolving process which has two distinctive phases that feedback into
each other—expanding and collapsing Expand and discover different
possibilities then narrow scope and focus We can use Untangle’s primitives
to force us to expand the possible solution space instead Let us
illustrate this by recreating one of the most famous computer art pieces
10 PRINT 10 PRINT is a oneline Commodore 64 BASIC program that generates a
visual pattern on the screen We can make a couple of boxes two symbols and
fill all boxes Using spatial queries to fill all of the boxes with
permutations of diagonal lines This already starts to look interesting but
we can get to more compelling results by adding additional constraints
Forcing more interesting results by applying inequality constraints And of
course we can introduce additional symbols and keep exploring the solution
space 10 PRINT variation using three symbols and two inequality
constraints Recursive rewrites We can apply the rewrites recursively by
flattening the pink results back onto the canvas and turning them into
black ink This will in turn update the spatial queries and generate a new
set of results New graphical reasoning models for understanding graphical
interfaces is a seminal paper on using graphical rewrite rules for
computation Progressively flattening solver results back onto the canvas
to create basic 1D cellular automata Recursive rewrites can be used in a
lot of interesting ways As an example below is a recreation of a logic
gates demo from Inkbase We start by creating the symbols And the rules
they follow Which shows us immediate feedback on the canvas We can then
set up some logic gate networks and propagate the values through them by
writing them onto the canvas to get to the final result A process of
propagating values through two logic gate networks Findings We have used
Untangle to solve the problems outlined above as we were building the
prototype to test our assumptions and intuitions We also conducted several
informal interviews with potential users with background in mathematics
and logic programming Here are some reflections from that process A smooth
ramp from concrete to abstract helps form intuitions about the system
Symbols queries and arrows build up on each other Arrows are a reified way
of moving a symbol into a box manually Spatial queries are a reified way
of selecting things manually Combining the two is a reified way of drawing
multiple arrows between multiple symbols “Reification” means giving a
concrete representation to an abstract process In this sense each
primitive is simply a way of expressing in more general terms what you
could already do in an earlier step Gradually climbing this ladder of
abstraction helps build intuition about how the system behaves Informal
solving is most useful for certain kinds of problems There seem to be two
dimensions of complexity for a given problem a problem can have relatively
trivial constraints but many elements that need to be solved or can have a
small number of elements but constraints that are difficult to satisfy
There is a sweet spot where Untangle seems most useful The dataset must be
small enough to be manually drawn but with constraints too complex to
easily solve in your head If the dataset is large it takes too much effort
to write it all down and the tablet screensize limits what can fit on the
canvas If the set of constraints is simple enough to keep in your working
memory you can often just solve the problem as you create its
representation without additional help from the computer We found that the
even a small number of overlapping constraints forces us to switch to
effortful “System 2” thinking and this is where Untangle shines helping us
think through a problem in an informal way Many problem representations
look like tables The way we naturally represent assignment problems tends
to drift toward using tables Examples of tablelike structures invented
adhoc to represent specific problems Even though a structured
approach—like a builtin table tool—might seem more appropriate to modeling
these kinds of problems freeform input feels important The exact shape of
the problem representation might not be clear initially and sketchiness
facilitates finding it It feels good to build up to a table rather than
being prematurely forced into one Another possibility is that the provided
spatial queries column with symbol at top row with symbol at left table
lookup etc encourage drawing problems in gridlike structures A rich area
for future work would be adding more ways to query the canvas which could
lead to more diverse representations Handdrawn input is well aligned with
exploratory problemsolving One of our motivations for handdrawn input was
to enable drawing symbols and elements that mapped closely to a particular
problem domain For example you could draw chairs and tables for a seating
arrangement In practice we rarely drew domain objects instead favoring
symbols like names logos or even dashes and dots However handdrawn input
still felt much more aesthetically fitting than the vector version we
tried early on Early iteration of Untangle using vector graphics and
artificial symbols At the lab we believe that the fidelity of the tool you
use should be proportional to the maturity of the idea you are working on
Being forced into crisp vector shapes for exploratory problems creates a
cognitive dissonance between the fuzzy nascent problem in our head and the
precise symbols on the canvas Fuzziness and live feedback contribute to a
conversational feel Untangle was designed to get the user to a result as
fast as possible Simply drawing a single arrow can generate multiple
results To find a satisfying solution it is often not even necessary to
add additional constraints Instead you can just scrub through proposed
solutions to find one that makes sense If you find a satisfying solution
you can simply stop working even if the results are underspecified In a
similar vein if the solver cannot satisfy your constraints rather than
showing an error message the system will attempt to ignore some
constraints relaxing the problem statement to generate a technically
incorrect solution The interface will highlight the arrows that were
ignored to generate each solution In realworld contexts we often are not
trying to find the globally optimal solution but rather just any
reasonable one Spatial queries are also fuzzy We do not look for something
“exactly 137px to the left” but “roughly to the left” This plays well with
handdrawn aesthetics as you never create perfect sketches Additionally
spatial queries highlight their matches directly on the canvas This has
two advantages first it helps explain what the query is doing—even if you
have no idea of the underlying formalism you can experimentally find out
what is happening Secondly it makes it transparent when the imperfect
matching algorithm does not work as expected You can always just wiggle
your drawing a bit to get the system to recognize it Finally arrows point
to and inside of queries rather than of connecting to ports This has a
specific informal feel which meshes well with the fuzziness of other parts
of the system and is distinctively different from the feel of things
snapping into each other Shortcomings The system lacks clear semantics
Untangle’s “language” is unspecified and not very composable The set of
provided spatial queries is adhoc We created new queries for problems we
were solving in the examples instead of building them up from first
principles As a result we can solve the examples nicely queries are not
composable or abstractable—you cannot combine to the left and to the top
to create the lookup query used in the coffee shop schedule nor can you
push the results from one query into another one to create reusable
functionalities Additionally creating these queries purely by example can
be quite tedious—especially when it comes to selecting wildcard
configurations It seems clear it would be better to create a match by
example then interactively refine it through direct manipulation One
exciting piece of research in this direction is described in Perceptual
Grouping Selection Assistance for Digital Sketching by David Lindlbauer et
al Most importantly it is hard to intuit how the primitives behave beyond
basic demos For example there is a subtle difference between constraining
elements of the solution space and constraining elements of the match
Careful thought is required to discern the difference Turning ink into
symbols is an unnecessary technical crutch Untangle is a system for
assigning candidate symbols to potential targets In our experience these
symbols often consisted of many ink strokes such as for people’s names In
order to assign these to a target we need to recognize those strokes as
being part of a grouping Using a magic wand to group multiple strokes into
a single symbol In past research we found that it was very difficult to
reliably and unambiguously group ink strokes or to recognize repetitions
For this project we simply sidestepped the problem with a command to
create a symbol out of a group of strokes This was convenient for a
research prototype but we feel this is unfortunate technical ceremony
Similarly when creating a drawing we encourage users to reuse copies of
the same target symbol to hint the solver system that those targets are
related Sometimes copying objects can be a fast and intuitive thing to do
Other times—especially when the shapes are simple—it feels more natural
just to draw them again and have them match automatically The history of
inferring specific user intent from ink gestures remains an open problem
after many years of related work including work on shape recognition for
drawing programs and back to early stylusbased text input systems such as
Palm’s Graffiti Some parts of the system lack visibility A computing
system should never leave a user feeling uncertain about whether the
intent of the user has been understood In Untangle assignment arrows are
freeform they can exist with or without valid sources and targets This
meshes well with the fuzzy aesthetic but our implementation does not
provide user feedback whether the arrow has actually connected the items
on the canvas other than the updated solutions For this specific example
it is easy to imagine how to improve this For example by color coding
arrows and connected spatial queries the same way we do for query matches
However color coding query components as well as their matches creased a
visually noisy rainbow canvas Finding the right queues and feedback for a
system like this is a subtle task There is a fundamental tension between
maintaining a focus on the user’s input by avoiding unnecessary UI chrome
and preventing confusion by providing sufficient feedback Responses from
the computer are underdesigned In systems where users and computers
collaborate it helps to distinguish between user input and computed
responses In Untangle user input is always black and we use pink to
distinguish computed results from userdrawn strokes We refer to this as
the user voice vs the computer voice Throughout our research we often want
the machine to respond and draw with us but what is the “correct” way to
do so Because Untangle limits user input to a single color rendering
results in pink makes the distinction immediately clear but we worry this
would become problematic in a more fullfledged system We briefly explored
rendering computed results using a different “pen” for example a stylized
marker but that felt uncanny—the user’s input strokes redrawn exactly but
with a different aesthetic Small canvas artificially constrains the
problem representation In Untangle the relatively small screen size and
lack of support for canvas features such as panning or zooming limits the
amount of data and the complexity of the problems you can represent
Drawing everything by hand also contributes to this limitation—it simply
requires too much effort to draw hundreds of student names or create a
staff calendar for an entire year We are interested in how the experience
of Untangle would evolve as we explored larger scale problems or more
complicated representations For example one future project we would love
to see is “Untangle with external data” There is no way to explore the
solution space One omission in this work is the limited ability to
visualize the solution space Yes we can narrow down the solution space by
reifying a result “Sam has to review Steve’s paper” or by adding
constraints “the wildcard cannot be the same as the contents of the box
next to it” but while Untangle allows you to “scrub” through results it
only ever shows one result at a time In fact the solution space is not a
homogeneous list there are recurring patterns It would be interesting to
explore visualizations that revealed clusters or branches of candidate
solutions that share similarities or how how different constraints “cut
off” certain areas of the solution space Conclusions With this project we
set out to discover what a nonbureaucratic theorem prover might look like
The traditional programming interface to a theorem prover is both strict
and formal Untangle shows a glimpse of a computational model with
fuzziness at its core Being able to handwave at a problem and get to
results—often on the first browse through the solution space—feels
wonderful and is a stark contrast Spatial queries provide a way to create
structure on top of a freeform drawing Instead of forcing problems
prematurely into tabular form you can start sketching the problem however
feels natural You then work with the system to query that diagram for a
satisfying solution In some cases the final result may take the form of
more traditional tabular data but we found that building up to it from a
freeform drawing and not being constrained by it prematurely allowed us to
explore our ideas more naturally The combination of symbols spatial
queries and arrows provides a nice onramp for abstracting logic Rules can
be built up out of simple examples gradually adding assignment arrows or
replacing those arrows’ concrete sources and targets with spatial queries
We feel this conceptual buildup is very promising and points at a possible
way of solving the repetition problem described in the Crosscut essay
Untangle is part of our “programmable ink” track of research continuing
from previous projects Inkbase and Crosscut We remain optimistic about
systems in which you directly manipulate the representation of the problem
at hand and that remain alive and reactive This combination allows you to
improvise and rely on intuitions instead of having to switch your thinking
mode to one of effortful logical computation We see here an exciting
glimpse of conversation with a dynamic medium—sketching at the speed of
thought and collaborating with the machine We welcome your feedback
inkandswitch or helloinkandswitchcom Thank you to everyone who offered
feedback and guidance throughout the project Peter van Hardenberg James
Lindenbaum Todd Matthews Kevin Lynagh Geoffrey Litt Scott Jenson Joshua
Horowitz Patrick Dubroy William Taysom Daniel Krasner Ivan Reese Paul Shen
Max Schoening
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Harnessing the Medici Effect for More Profound Web3 Impact CARBON Copy
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OpinionHarnessing the Medici Effect for More Profound Web3 ImpactHow we
have strayed off the path of originality and how to get back on itBy
Trinity Morphy May 21st 2024In this piece Trinity Morphy takes inspiration
from a recent event to look at why originality has been so difficult to
attain in the Web3 impact space and how a phenomenon called the Medici
Effect can get us back on trackI had the privilege of attending a Green
Pill Nigeria Impact Tour event two weeks ago In his talk Izzy the lead at
Green Pill Nigeria pointed out the troubling trend of imitation in the
impact space Each cycle he said seems to be filled with recycled project
ideas It has become customary for Project XYZ to emerge with a seemingly
novel concept only to be quickly followed by Project ABC essentially a
copycat with a new bell or whistleThis lack of originality especially in
Web3 impact is not just a hurdle its a roadblock For instance other
effective ways exist to utilise impact NFTs apart from sequestering carbon
or planting new trees Yet we keep seeing new projects based on the same
idea but with a more exciting descriptionHow can we actively encourage a
shift from simple recycling to genuine originality The Medici Effect that
the most innovative ideas happen when you combine concepts from different
fields offers insight By looking beyond the impact field we can unlock the
potential for more impactful solutionsWhy we recycle ideas and why
originality is so importantpictwittercomsRtpkwgMGk— OwockiΞth owocki May
17 2024Reduced risk and familiarity Humans naturally gravitate towards
familiarity Replicating a successful project offers security by minimising
the uncertainty of venturing into something completely new Its like
following a wellworn path instead of forging one through the
wildernessAccess to funding Investors and funding institutions are more
likely to back sectors with a proven track record of projects A copycat
project can point to the success of the original and argue that it can
replicate that success with its own twistBandwagon effect When a project
becomes popular others aim to capitalise on the hype and user base On the
surface launching a copycat project appears easier as does the marketing
that goes with itAvoiding mistakes A successful project has already
learned what works and what does not Emulation enables new projects to
sidestep those pitfalls and concentrate on innovationOriginality is
crucial to tackling our social and ecological problems It allows us to see
things differently question assumptions and uncover new possibilities This
fresh perspective can lead to new solutions we would not have considered
otherwise It empowers us to challenge outdated or dysfunctional systems
and propose solutions that address their shortcomings from the ground up
Original thinking enables us to recognise the potential in underutilised
resources and address problems at their roots not simply treat their
symptomsEasier said than done of course We need to look to the Medici
Effect for a roadmapThe Medici Effect and Web3 impactThe Medici Effect
states that the most original and extraordinary ideas occur when you
combine concepts from different fields disciplines or cultures It was
discovered by Frans Johansson and shared in a book of the same name A
majority of the ideas in this section are borrowed from the book and
modified to fit Web3 impactSome examples of great products that have
stemmed from the Medici Effect include Silvi reforestation Web3 M3tering
Protocol renewable energy distribution Web3 Gitcoin fundraising Web3 and
Toucan Protocol voluntary carbon markets Web3Heres how we can get better
at using the Medici Effect to our advantageDismantle the barrier between
Web3 and other fieldsFirst we must be willing to break the associative
barriers that exist between Web3 and other fields How do we do this
Through exposure to a diverse set of cultures Culture in this context
extends beyond geographic boundaries to encompass ethnic class
professional and organisational differences By immersing ourselves in
these diverse backgrounds we can unlock a more open and questioning
mindset and challenge our assumptionsWe also need to embrace broad
selfeducation Traditional education often compartmentalises knowledge but
selfdirected exploration across disciplines expands what is possible
Without it our thinking is limited and we inadvertently stifle creativity
Selfeducation empowers us to discover unexpected connections and envision
how concepts in other fields can combine to create groundbreaking Web3
impact solutionsCombine random conceptsIntersectional ideas are
groundbreaking because the concepts involved are so different and the
combinations so unusual that no one would have thought them possible Take
the inspiration for this article as an example It happened after I came
across an X account named Cozomo de Medici I was not thinking about Web3
impact or the Medici Effect That Is how random combinations work You have
no control over it It just comes Rather than leaving luck to do the work
we can continuously stimulate our brains to keep producing these random
combinations How do we achieve thisNurturing our curiosity By obsessing
over new ideas approaches and perspectives we enhance our brains ability
to blend random concepts In the foreword of Exploring MycoFi Scott Morris
pointed to Emmett Jeffs relentless fascination with mushrooms and mycelial
networks and how it led to the creation of MycoFi a novel cryptoeconomic
model inspired by the structure of mycelial networksInteracting with
diverse groups of people Engage a diverse group of people and we will be
presented with a diverse set of perspectives Interacting with such groups
can spark unexpected connections For example a conversation between a Web3
enthusiast and a custodian of tradition might lead to an idea to preserve
cultural heritage using blockchainThese are what create the conditions for
the next phaseIgnite and evaluate an explosion of ideasThe strongest
correlation between quality and quantity of ideas is in fact the number of
ideas Do you know how many ideas you can get by simply combining concepts
from environmental science with Web3 concepts A LOT That is why it irks me
when I see so many projects centering on carbon credit tokenisation when
there are so many ideas yet to be explored The question here is once these
ideas start flooding in how do we handle themFirstly capture as many ideas
as we can Keep track of all the ideas our brains generate and set a target
to reach before evaluating their feasibility Secondly we need to take our
time evaluating because our minds will quickly judge the value of an idea
by comparing it to what is already known to work Its important that we
evaluate each idea as sincerely as the next whether its gamifying
traditional classroom learning or eradicating open defecation in
underserved communitiesComing up with great ideas does not guarantee
innovation however We must make those ideas happenMake intersectional
ideas happenThe paradox of innovation at the intersection of fields is
rooted in the symbiotic relationship between ideas and failures the more
ideas we explore the higher the rate of failure Far from being a negative
consequence failures are a vital part of the innovation journey We learn
and grow through them so that we can do better the next time Not acting
for fear of failure robs us of this crucial phaseDaring to try ideas opens
us to a world of invaluable insights that help us refine our approach
identify weaknesses and ultimately discover the path to a truly
groundbreaking solution In my interview with Christwin of Switch Electric
and M3tering Protocol he shared a fascinating story about the early days
of his solution The first model they tried unexpectedly incentivised the
consumer to overload the solar infrastructure leading to severe component
wear and tear and attracting steep maintenance costs This was a
significant failure but it led to research that brought about the idea of
building M3tering Protocol on blockchain to track consumption and ensure
transparencySince failures are inevitable we can allocate specific
resources for testing each new idea and minimising the potential for
catastrophic failure This allows for rapid iteration where we can learn
from each attempt refine our approach and move on to the next experiment
with valuable insights Do Not forget to document everything along the way
and share the results within the team This knowledge base becomes a
valuable resource for future projects because it prevents the same
mistakes and accelerates future breakthroughs We saw this in the
transition from Gitcoin 10 and Gitcoin 20We also need to stay motivated
along the way because the path to ingenuity is rarely linear There will be
setbacks and failures that make us question our actions Staying motivated
requires keeping the longterm vision in mind and focusing on the positive
impact our work can bring to the world We need to celebrate all wins big
and small whether its successfully completing a pilot project achieving a
user engagement milestone or receiving positive feedback from a target
community This reinforces our belief and helps us pushing forward despite
the inevitable setbacksConclusionThe Web3 impact space has potential to
change the way we tackle the worlds most pressing challenges Were not
getting there however if we keep recycling the same old ideas Originality
is the key if we are to truly unleash Web3 impact We must look beyond our
own siloes break down barriers and ignite curiosity across a variety of
fields to spark the kind of breakthrough ideas that will move the
needleAnd when those ideas do come we must not shy away from failure and
its valuable lessons Nature exemplifies this beautifully a butterflys
struggle to escape its chrysalis is anything but pleasant Still this phase
is necessary for the butterfly to strengthen its muscles expand its wings
and ultimately fly Embrace the journey celebrate even the smallest wins
and surround yourself with a supportive network Together we can embrace
the power of the Medici Effect to create a better future for ourselves and
the planetThis article represents the opinion of the authors and does not
necessarily reflect the editorial stance of CARBON CopyCopyright © 2025
CARBON CopyToken data provided by CoinGeckoFront PageFeaturesLearnReFi
ProjectsAboutSubmit News
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5 DeSci projects disrupting scientific research and development — Crypto
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DeSci projects disrupting scientific research and development Project
HighlightsScienceDAOs Mar 30 Written By Drew Simon 2021 was the year of
decentralization and this momentum has only increased into 2022 Not only
have we seen incredible growth in the decentralized finance DeFi space but
we have also seen the emergence of social impact DAOs decentralized media
platforms decentralized VC funds and more recently the emergence of a new
field – Decentralized Science or DeSci In short “the decentralized science
DeSci movement aims to harness new technologies such as blockchain and
‘Web3’ to address some important research pain points silos and
bottlenecks” Whereas scientific research has long been viewed as overly
bureaucratic and disjointed the DeSci movement aims to improve this by
using blockchain to offer greater transparency and to take on the “profit
hungry intermediaries” such as scientific journals that have dominated the
traditional research spaceFor some resources on DeSci I recommend you
check out the following articlesDeSci an opportunity to decentralize
scientific research and publicationA Guide to DeSci the Latest Web3
MovementCall to join the decentralized science movementFor this blog post
we will be highlighting 5 DeSci projects that are leading the way and
positively disrupting scientific research and development1 VitaDAOOne of
the best examples of DeSci in action is VitaDAO a Decentralized Autonomous
Organization DAO focused on funding longevity research in “an open and
democratic manner” Specifically they are focused on the decentralization
of drug development focused on the extension of human life and healthspan
They fund earlystage research with the goal of turning the research into
biotech companiesVitaDAO is government by holders of VITA tokens which can
either be purchased or earned through contributions of work or
intellectual property With over 4000 members and 9M in funding raised to
support scientific research VitaDAO has proven that the DeSci movement is
no laughing matterCheck out some of their featured projects here2
SCINETThe SCINET platform which is built on blockchain enables retail and
institutional investors to securely invest in scientific research and
technology directly In addition to funding promising scientific research
they also offer a “blockchainpowered” cloud laboratory for researchers a
rigorous decentralized peer review process and enable researches to
document their IP on an immutable blockchain3 AntidoteDAOAntidoteDAO is a
decentralized community focused on funding cancer research and other
cancer initiatives Their ecosystem includes a governance token and NFT
collection which both enable individuals to vote on where to allocate
funds In addition to providing funding to charities supporting cancer
research and cancer patients a core focus of the DAO is on providing 100K
seed fund grants to cancer research teams Research projects are first
reviewed by the DAO’s Medical Advisory team and then put to the community
for a vote Fun fact we have an upcoming podcast episode with AntidoteDAO
that when available will be published HERE Crypto Altruism uses Ledger to
keep its assets safeYou’ve probably heard the phrase “not your keys not
your coins” By choosing a hard wallet like the Nano S Plus to store your
crypto you can rest assured that the keys and the crypto are truly
yoursGet your Ledger Nano S Plus now by clicking HERE or on the image
below 4 LabDAOLabDAO is an emerging organization which is dedicated to
operating a communityrun network of wet and dry labs with the goal of
advancing scientific research and development A wet lab is one focused on
analysing drugs chemicals and other biological matter whereas a dry lab is
one focused on applied or computational mathematical analysis LabDAO is a
relatively new project that is still in its infancy but has a promising
mission and strong community of support around it 5 MoleculeMolecule is a
decentralized scientific research funding platform that operates as a
marketplace for researchers seeking out funding and individuals looking to
invest in scientific research projects They are “connecting leading
researchers to funding by turning intellectual property and its
development into a liquid and easily investable asset”Researchers can list
their research projects on the Molecule marketplace as a means to engage
with potential investors and to secure funding for their project Molecule
currently has over 250 research projects listed on their marketplace over
4500 DAO community members and 3 “Bio DAOs” with over 10M in funding in
their network According to Molecule “The future of life science research
will be driven by open liquid markets for intellectual property powered by
web3 technology”We cover more amazing DeSci projects in our more recent
postTen more DeSci projects disrupting scientific research development and
knowledge sharing Buy me a coffee Send a tip in ETH cryptoaltruismethLike
what you are reading Consider contributing to Crypto Altruism so we can
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DeScidecentralizationscienceblockchainlists Drew Simon Previous Previous
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A Short History of BiDirectional Links Home The Garden Essays Notes
Patterns Smidgeons Talks Podcasts Library Antilibrary Now About The Garden
Essays Notes Patterns Smidgeons Talks Podcasts Library Now About Essays
evergreen A Short History of BiDirectional Links Seventy years ago we
dreamed up links that would allow us to create twoway contextual
conversations Why do not we use them on the web Design Digital Gardening
The Web Web Development Planted almost 5 years ago Last tended about 4
years ago Table of Contents Bidirectional links are not new Bidirection
Linking in Personal Digital Gardens Building Your Own BiDirectionals
BiDirectional Linking with WebMentions Table of Contents Bidirectional
links are not new Bidirection Linking in Personal Digital Gardens Building
Your Own BiDirectionals BiDirectional Linking with WebMentions With the
recent rise of Roam Research the idea of bidirectional linking is having a
bit of a moment We are all very used to the monodirectional link the World
Wide Web is built around They act as oneway pointers we follow in a linear
sequence While we can link to any site the destination page has not a clue
we have done so We set up all these singledirection paths trying to signal
relevance and context only to have the other side completely ignore our
efforts Our monolinks are trying to establish relationships in vain We are
starting to look around our monolinked environment and wonder why it is so
hard to surface relevant contextual relationships Manually interlinking
content takes an awful lot of human curation and effort Efforts we should
probably slog off onto our systems Enter the bidirectional link A
bidirectional link has social awareness it knows about other pages or
‘nodes’ that point to it and can make them visible to people This means we
get a twoway conversation flowing between our web locations Bidirectional
links are not new The idea of the bidirectional link goes back to 194580ya
when Vannevar Bush dreamed up the Memex machine Vannevar outlined this
hypothetical gadget in an essay in The Atlantic called As We May Think He
wanted a system capable of “associative indexing… whereby any item may be
caused at will to select immediately and automatically another… so that
numerous items have been thus joined together to form a trail” This essay
turned out to be a foundational document for the ideologies that directly
led to both the internet and the Web Yes those are two entirely separate
pieces of technology Vannevar was one of the key movers and shakers
rallying folks to help build the original internet infrastructure He
corraled folks at MIT the US Department of Defence the National Science
Foundation and various research labs like the Standford Lincoln Lab Bell
Labs the RAND Corporation and Xerox PARC to get involved Walter Isaacson
The Innovators How a Group of Hackers Geniuses and Geeks Created the
Digital Revolution London Simon Schuster 201510ya Suffice to say the guy
was driven by a belief that enabling people to connect information and
share knowledge would expand the scope of human understanding The Memex
was one idea of how that might manifest in material form Vannevar even
created a small informative diagram of this deskbound vision Marketing
chops 101 Vannevar’s evocative description of the Memex is especially
impressive given that digital computers had only come into existence 5
years earlier Most were still the domain of large military operations like
Bletchley Park and were seen as inconveniently large calculators
Implementing a wildly interactive computational personal knowledge base
was not much of an option So the idea went into hiberation and did not
resurface until the idea of personal computing began blooming in the
sixties and seventies Ted Nelson an unlikely film director and sociologist
stumbled into a series of computing lectures and began to imagine how
graphical interfaces might reinvent the way we write and connect ideas He
took inspiration directly from Vannevar’s essay and in 196560ya when he
coined the term hypertext to describe his vision for a sprawling network
of interlinking information Nelson planned to implement these hypertextual
dreams in his perpetuallyimminent Project Xanadu If you have some time
this is quite the internet history rabbit hole to run down Ted Nelson is
on another level The Xanadu project was a hypertext system that imagined
that every sentence block and page would be part of a vast bidirectionally
linked network A design mockup of how Project Xanadu might visually
connect pieces of text across multiple documents You would be able to
trace information back to its origin the way current web links do But you
would also be able to see who had referenced remixed and expanded off that
original The full Pattern Language of Project Xanadu expands far beyond
just bidirectional links to include features like Transclusions but we
will not dive into it all here Suffice it to say Xanadu did not pan out
Instead we got the less fancy but far more real and useable World Wide Web
that currently does not support bidirectionals on an infrastructure level
While Sir Tim Berner’s Lee wrote himself a note debating their pros and
cons back in 199926ya there is an obvious design issue with letting twoway
connections flow freely around the web If every site that linked to yours
was visible on your page and you had no control over who could and could
not link to you it is not hard to imagine the Trollish implications…
Figuring out how we might filter moderate and set permissions around link
visibility turned into quite the challenge The design details grew complex
It became clear implementing the Web with simpler monodirectional links
was the right thing to do given that its creators wanted universal
adoption Lots of people are still mad about it Let us not venture too far
down that historical wormhole The TLDR is technology is hard Until Xanadu
ships and we are all immersed in the universe of multilinked
versioncontrolled nodes of remixable microcontent that somehow solves the
problems of permissions and moderation there are still plenty of ways we
can resurrect the possibility of bidirectional links on the web
Bidirection Linking in Personal Digital Gardens Most of the design issues
with adding bidirectional links to the global web were related to
moderation and permissions However adding them within the bounds of a
single website with one author sidesteps that problem There is been a
flurry of interest around bidirectionals among people involved in the
Digital Gardening movement Much of this was originally sparked by Andy
Matuschak’s notes Go have a good browse through them Andys linked notes
stack on top of one another allowing you to browse to new notes while
previous notes are still visible There is plenty to admire here It should
be noted Andy is an experienced developer and interaction designer and
these notes should not be taken as the standard expectation for the rest
of us normal plebby internet citizens But the key part of this system that
creates interlinked context is the “Links to this Note” section at the
bottom of each post Anytime Andy links to another one of their notes on
the site it will pop up as a related note at the bottom of the page This
is the bidirectional dream It gives us a way to navigate through these
ideas in exploratory mode rather than navigating a hierarchy of categories
on a main index page Since it is all contained within a singleauthor site
our SpammishTrollrisk factor is at a comfortable zero This is mildly
tangential but I love how the topic of bidirectional links makes fully
visible our “websites are locations” and “websites are containers”
conceptual metaphors with “inside” and “outside” links Building Your Own
BiDirectionals That is all very cool but how are you supposed to build
bidirectionals into your own site Thankfully setting up your own public
gardening bidirectional Memex does not involve Xanadu One fantastic option
for nondevelopers is based around a personal wiki system called TiddlyWiki
AnneLaure Le Cunff wrote up an easytofollow guide to getting your own up
and running For those of us here for the hypercustomised overengineered
JavaScript solution that would be me the Gatsbyjs community has a number
of active gardening enthusiasts building themes and plugins I built mine
using Aengus McMillin’s gatsbythemebrain Aengus has documented the theme
well and it is not too challenging to implement as long as you are
comfortable in JavaScript and React I also curate a list of tools for
Digital Gardening on this Github repo BiDirectional Linking with
WebMentions While I argued that Webwide bidirectional links are unlikely
to happen at a global scale there is a way you can add bidirectionals to
your personal website that picks up on references anywhere on the web
WebMentions are a piece of web infrastructure the IndieWeb community has
done a lot of work to advocate for The W3C gave the specification
recommendation status in 20178ya The system notifies a URL whenever that
site is mentioned elsewhere on the web You are then able to show that
mention and its contents on your site It is essentially an optin
bidirectional linking system Plenty of folks have written useful guides on
how to add these to your site Here is one for any static site one for
Gatsby one for Nextjs There is a whole list of implementation examples on
the IndieWeb Wiki you can look through 5 Backlinks A Brief History Ethos
of the Digital Garden A newly revived philosophy for publishing personal
knowledge on the web Digital Gardening for NonTechnical Folks How to build
a digital garden without touching code Transclusion and Transcopyright
Dreams The lost permissioning and copyright system of the Web The Pattern
Language of Project Xanadu Project Xanadu as a pattern language rather
than a failed software project A MetaTour of This Site A video tour
through how I build the old version of this site Mentions around the
webCarlos Sanmartín Bustosmentioned in En busca de enlaces
bidireccionalesJune 24 2024Una de las cosas que echo en falta al haber
pasado el blog a un sitio estático son los links bidireccionales No tanto
los links que provengan de fuera que hoy en día van a ser mínimos como los
links internos que permiten explorar el blog por ejemplo para avanzar
hacia el futurAngsuman Chakrabortymentioned January 07 2023A Short History
of BiDirectional Links CypherNewsmentioned January 04 2023 Hacker News A
short history of bidirectional links 2020 hackernews HN Front
Pagementioned January 04 2023A Short History of BiDirectional Links L C
newsycombinatorcomitemid342447…Winson Tangmentioned January 04 2023A short
history of bidirectional links 2020 Hacker Newsmentioned January 04 2023A
short history of bidirectional links 2020 Patrick Durusau ⏳ White Person
on White Supremacymentioned May 18 2022codexeditor I Have lost the tweet
where I saw this mentioned earlier today I like the Web Mentions idea esp
if we could use XPath to point to less than the page level Thoughts Show 3
more Want to stay up to date Subscribe via RSS Feed © 2025 Maggie Appleton
The Garden Essays About Notes Now Patterns Podcasts Talks Smidgeons
Colophon Library
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Part 1 Introduction to Responsible Technology by goodbot MediumOpen in
appSign upSign inWriteSign upSign inPart 1 Introduction to Responsible
TechnologygoodbotFollow11 min read·Aug 3 2023ListenShareIntroductionIn
late 2022 the GoodBot team — consisting of a group of sociallyminded
professionals working in law technology and policy — came together to
develop a snapshot of Canada’s current Responsible Technology landscape
This is a space that to date had been heavily defined by voices from the
United States Our goal is to understand the Canadian ecosystem’s current
composition capacity and direction particularly how technology impacts
Canadians what issues are of focus in research and programming and how the
policy landscape is evolving at the provincial national and international
levelsTechnology is revolutionizing everything from healthcare to
education to law to climate science and government but is also associated
with a wide range of risks and harms making responsible technology
governance a critical priority for governments nonprofits and marketsNew
visions clear policy frameworks effective implementation methods and
multistakeholder oversight bodies are needed to navigate this landscape It
also requires public interestfocused strategic collaboration that
includeslongterm research on harmsmore transparency and collaborative
efforts with technology companies to strengthen safetyeffective mechanisms
to hold companies accountable when they fail to act in response to
harminvestment in public interest technology and philosophies that
prioritize healthy technology ecosystemsunderstanding the leverage points
and incentive systems that contribute to these outcomes andthe development
of the critical capacities needed to meet this momentWe know from the last
two decades that when technology tools and platforms become deeply
embedded in institutions like media and education before they are
regulated they become harder to govern This reality has led to escalating
and lasting harm in a number of areas The pressing question now is how to
forge a new direction recognizing the immediate need to take actionThis is
the introduction to a research project on Canada’s Responsible Technology
landscape GoodBot’s goal with this research is threefoldTo understand the
current landscape and priorities of Canada’s Responsible Technology
ecosystem including the who what where and howTo highlight gaps and
opportunities within this ecosystem that can help Canada develop a more
robust impactful and collaborative approach and agenda andTo understand
what role GoodBot can play in advancing Responsible Technology at home and
around the worldWhat is Responsible TechnologyResponsible Technology acts
as an umbrella for a range of approaches and terms that all focus on
different issues or specific intervention points in technology and
business life cycles It includes concepts such as ethical tech humane tech
tech stewardship and public interest tech all of which are connected and
overlap but which also center on different locus of influence These and
other terms will be explored in Part 1 of our seriesResponsible Technology
is a relatively new framing that includes a wide range of issues related
to technology Some issues — like privacy and freedom of expression — are
longstanding cornerstones of the most established technology nonprofits in
the country while conversations on Generative AI risks are relatively new
Yet technology and AI ethics have been around for decades with themes
prominent among academic labs human rights defenders peacebuilders and in
other convening spaces What has changed is the scale and pace of
technology and the amplification of new risks and narratives surrounding
technology harms These have created a growing awareness of the need for
safetyfocused design and research at the outset meaningful oversight of
technology companies and effective accountability mechanisms when
companies fail to act in the public interestMany technology tools and
businesses currently fail to meet even a vague understanding of
Responsible Technology This is especially true for small to medium
technology companies who focus on survival and leave proactive assessment
and harm mitigation as an afterthought if they get any attention at all
Others have social impact strategies that are completely detached from
their business modelFew companies start with the goal of causing harm but
unintended consequences can arise due to a lack of intentional
consideration capacity and unanticipated and conflicting priorities
Additionally as products scale seemingly harmless matters can lead to real
harm as user bases grow use cases expand and incentive structures change
The explosive emergence of generative AI has made it even more clear that
left unaddressed these structural factors risk widening the gap between
privatized profit and socialized riskIn spite of these growing concerns
several Big Tech companies have chosen to lay off large segments of their
Trust and Safety teams seeing them as cost centers that add undesirable
operational complexity Even when companies have Trust and Safety teams in
place they are often pitted against product teams The result is companies
that increasingly seek to automate these decisions which frequently and
disproportionately impact minority communities including human rights
defendersSome companies have begun sharing Transparency Reports which is a
move in the right direction However there are no agreed standards or
metrics against which to assess companies’ commitment to social
sustainability nor is there any external oversight These factors lead to
the possibility of ‘tech washing’ and cherrypicking data that provide the
appearance of taking action but in ways that lack substantive effect or
because new harmMoreover even companies that have the desire to act
responsibly can lose sight of their original goals when they face demands
for outsized returns from investors — including venture capitalists and
private equity investors — which can place them at odds with decisions
that are in the public interestIn this context a wide range of social
harms and externalities have arisen — many of which are unintentional —
and which includeBiased Unaccountable Untransparent AutomationBias in
untransparent algorithms that discriminate against marginalized
groupsDisruption of the workforce by generative AI in almost all
professional sectorsBig Tech DominationBig Tech market domination to
control value chains through predatory pricing terms and
acquisitionsNonconsensual selling of personal data to and from thirdparty
data brokersAddiction Mental HealthThe use of dark patterns to drive
engagement and addiction in gaming and social mediaThe decline of
attention spans at a population level in the last 20 yearsThe decline in
mental health and body image especially among youth leading to self harm
and deathHarassment Violence ExtremismIncitement to radicalization
extremism and even genocideTrolling doxing and harassment including
targeting women trans and BIPOC peopleBad ActorsTargeted and opportunistic
disinformation and microtargeting to undermine democraciesScams to steal
millions from people through generative AI or with crypto hacksTrafficking
of women and girls on the dark web and in mainstream platformsThis is by
no means a comprehensive list In response Responsible Technology advocates
have advanced efforts in recent years to understand the wide array of
externalities impacting different levels of society These initiatives
variously aim to understand harms and causes increase public awareness and
engagement incentivize governments to enact new laws and enforce existing
ones and create solutions that lead to safer and more responsible
technologyenabled environmentsAdditionally a new wave of government and
nonprofit investigations and litigation aims to clarify technology
companies’ responsibilities and identify leverage points to incentivize
responsibility These efforts have had some successes but are often too
incremental and underresourced to keep paceThe scale and complexity of
issues arising from technology are unprecedented Canada needs a clear
Responsible Technology agenda and sufficient investment to move toward a
technological future defined by healthy people businesses markets
societies and democraciesThe Asymmetry Sustainability GapA key barrier
facing Responsible Technology advocates — including journalists academics
tech nonprofits technologists tech ethics experts policymakers and
citizens — in addressing technology harms is an existing and growing set
of asymmetrical disadvantages when compared to the companies and sectors
responsible for harmThese disadvantages manifest in many forms including
limited access to talent data sets algorithms infrastructure information
internal research and audits knowledge and resources It shows up in access
to capital restrictions on how capital can be used and comparatively
robust ethical requirements It is further exacerbated by companies’
anticompetition tactics to buy out underprice feature bundle and otherwise
aggressively quash any disruptors who may be able to offer healthier
alternativesAdditionally asymmetries show up when comparing the inputs and
outcomes around harm It is — for example — much less resource intensive to
create campaigns to disseminate disinformation on vaccines — than it is to
undo the damage caused by this disinformation This reality places a
societal premium on considering what effective oversight governance and
accountability of technology look like but also raises the need to balance
corrective actions with Freedom of Expression FoE norms The global nature
of many technology platforms means that US norms are effectively imposed
on Canada and other countries Yet Canada has its own unique and
wellestablished interpretations of fundamental freedoms that should be
considered and protected in the face of technological changeCanada’s
Responsible Technology ecosystem is small and underresourced compared to
its US counterparts and at this time there are few prominent
ecosystemlevel organizations that are wellpositioned to guide a
Responsible Technology community and strategy Yet to effectively influence
outcomes Responsible Technology advocates need to work together including
by establishing new governance innovationsA critical factor in the
Canadian context is that much of the funding to date has focused on
understanding symptoms and immediate causes rather than underlying
structural issues and incentive systems at play Some of this is a product
of new and emerging organizations with limited track records while other
issues arise from inadequate and restrictive funding and opportunities
Some organizations only work on technology matters at a project level
rather than a mission level Such factors are important to understanding
the limitations on Canada’s capacity and sustainability Our sixth report
will explore Canada’s nonprofit capacity in more depthAn additional
barrier is that there are no obvious market solutions to address many of
the problems that arise from technology For example while technology has
led to unprecedented online harassment of women people of color and LGBTQ
communities companies offer limited solutions aimed at limiting
harassmentThis reality is exacerbated by the fact that markets recently
rewarded technology companies for cuts that significantly depleted their
Trust Safety teams even when it occurred at a time of high salience around
the risks posed by technology platformsLack of coordination is also a
factor among tech companies For example some companies argue that if they
do not employ harmful tactics such as polarizing content or algorithms to
attract attention they will lose out to rivals who will These realities
point to an increasing need for sectors to collaborate toward reducing
harm and promoting public interestIndeed in areas where companies have
invested more material resources — including to address extremism and
protect children — even Big Tech lacks the bandwidth to address the
complex range of issues on its own making collaboration essential Within
the tech sector new multistakeholder initiatives such as Global Internet
Forum to Counter Terrorism and the Tech Coalition have been launched in an
effort by technology platforms — and include human rights advocates
governments and researchers — who work collectively to reduce extremism
and child sexual abuse material online respectively Such issues are even
more challenging for smaller platforms and startups that lack internal
resources to respond to emerging and unanticipated issuesUltimately while
technology companies contribute many benefits to society they also
contribute significant problems that neither society the markets nor they
are presently able to solve They often lack incentives to prevent and
address problems up front and even when they want to do the right thing
investor incentives can derail their decisions There are limited market
incentives to address challenges created by businesses and market
competition Moreover our governance institutions operate in ways that are
incompatible with the fastmoving pace of technology which presently tend
to focus on harm to individuals instead of on harm to society These
factors together mean that we are in a situation that is by definition
unsustainable We need collective action to address these risks including
through responsible resources capacities frameworks budgets and
policiesCanada’s Policy LandscapeWhile several technologyfocused bills are
in development Canada’s current policy landscape is far behind the
advances of the last 20 years This is also true of many other countries
that currently lack the policies capacities institutions and enforcement
mechanisms needed to govern a rapidly evolving technology environment
Furthermore research shows that even where effective policies are in place
underresourced enforcement mechanisms such as antitrust hamper the ability
of governments to enforce existing laws In this context the role of civil
society organizations is particularly importantWhile the policy landscape
is expected to evolve rapidly we do not know what effect these policies
will have or how coherent they will be across jurisdictions and issues
Canada has introduced many bills for consideration but few have passed and
all leave much to be desired In the intervening time legal firms and the
Privacy Commissioner have advanced litigation — with a particular focus on
privacy and antitrust — to hold technology companies accountableCivil
society organizations often lack consensus on addressing key issues For
instance Online Harms advocates support stricter content moderation to
tackle harassment extremism and child exploitation In Canada some lean
towards Freedom of Expression while others recognize the need to address
such harms but fear that wellintentioned policies could inadvertently
suppress the voices of vulnerable communities Balancing these competing
rights is complex Responding to emerging issues and harms that affect us
all requires better public engagement This includes open and inclusive
dialogue transparent consultation processes and effective accountability
mechanisms to navigate these complexities and to help uphold and balance a
range of fundamental Canadian rightsIndeed there are no ‘right’ answers
but rather ‘different tradeoffs’ Moreover there are ways to escape such
polarity traps which can easily become politicized resulting in deadlock
Even among nonprofit organizations such as the ones that are seemingly at
odds on online harms for example both largely agree that passing
comprehensive privacy frameworks would mark an important victory and
achievementYet even if we achieve effective regulation and enforcement
addressing entrenched asymmetries — especially those caused by Big Tech —
requires a collective agenda and roadmap What is clear is that our current
institutions lack the capacity and resilience needed to address the
challenge we faceAs Canadians we have an opportunity to draw upon the
values that make us strong as we reimagine our relationship with
technology Ideas such as Indigenous approaches to data sovereignty
collaboration and multiculturalism have much to teach us about how to
navigate these complex issues This moment presents an opportunity to
rethink and localize the who how and why of technology governance This is
both a daunting and an exciting challengeOpenSourcing GoodBot’s
ResearchFor GoodBot our first step is to practice our open principles by
sharing what we have learned We hope that this research can lay the
groundwork for building a Canadian coalition to support its nascent and
necessary Responsible Technology movementGetting to impact requires
understanding Canada’s existing capacity understanding the systemic issues
at play exploring moral and policy considerations surfacing current and
emerging asymmetries of power and exploring how AI is upending companies
and industries It also requires a collective strategy and targeted action
focused on moving toward responsibilityThese documents are intended to act
as a primer for anyone seeking to make an impact in addressing critical
priorities facing Canada and the world While our early research may
initially be of more value to nonprofits and academics and should be
considered a WorkinProgress we aspire to a future where solutionsoriented
multistakeholder collaboration is a new norm Our research will be broken
into two partsPart 1 is a Canadian Responsible Technology Landscape that
explores common terms civil society stakeholders current and emerging
policies and litigation and how asymmetries of power manifestPart 2
reviews the results of a survey conducted key observations on the current
and emerging landscape and critical reflections on how to strengthen
interdisciplinary collaboration among nonprofit organizations academia the
tech sector and governmentIn an ideal world this work will lead to
highlevel consultations and strategies developed in collaboration with
other ecosystem organizations motivated to move this conversation
forwardCanada as a Global Leader in Responsible TechDespite and perhaps
because of the wide array of challenges Canada has an opportunity to
become a global leader in developing deploying and governing technology in
socially sustainable ways Getting there requires an urgent focus on
strengthening national capabilities by investing in strategic and
systemsfocused multistakeholder mechanismsIndeed organized effectively
Canadian civil society represents critical and untapped assets to help
meet this moment There is also a need to strengthen citizen education
advance responsible policy and oversight create technical solutions to
advance the public interest introduce responsible technology certifiers
and respond to systemic factors that lead to harmful outcomes Canadians
can no longer afford to wait The time to engage is nowVersion 10 July 2023
Written by Renee BlackFollowWritten by goodbot3 Followers·1
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yetHelpStatusAboutCareersPressBlogPrivacyRulesTermsText to speech
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: false
base_model: sentence-transformers/paraphrase-mpnet-base-v2
model-index:
- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: Unknown
type: unknown
split: test
metrics:
- type: accuracy
value: 0.5517241379310345
name: Accuracy
SetFit with sentence-transformers/paraphrase-mpnet-base-v2
This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-mpnet-base-v2 as the Sentence Transformer embedding model. A MultiOutputClassifier instance is used for classification.
The model has been trained using an efficient few-shot learning technique that involves:
- Fine-tuning a Sentence Transformer with contrastive learning.
- Training a classification head with features from the fine-tuned Sentence Transformer.
Model Details
Model Description
- Model Type: SetFit
- Sentence Transformer body: sentence-transformers/paraphrase-mpnet-base-v2
- Classification head: a MultiOutputClassifier instance
- Maximum Sequence Length: 512 tokens
Model Sources
- Repository: SetFit on GitHub
- Paper: Efficient Few-Shot Learning Without Prompts
- Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts
Evaluation
Metrics
| Label | Accuracy |
|---|---|
| all | 0.5517 |
Uses
Direct Use for Inference
First install the SetFit library:
pip install setfit
Then you can load this model and run inference.
from setfit import SetFitModel
# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("praisethefool/human_tech-fields-multilabelclassifier")
# Run inference
preds = model("5 DeSci projects disrupting scientific research and development — Crypto Altruism 0 Skip to Content BLOG CATEGORIES DAOs EDUCATION ENVIRONMENT REFI EQUITY INCLUSION FINANCIAL INCLUSION DEFI NFTs PHILANTHROPY SCIENCE DESCI SOCIAL IMPACT SUPPLY CHAIN COMMENTARY PODCASTS CRYPTO ALTRUISM PODCAST THE WEB3 NONPROFIT IMPACT ON OPTIMISM INFOGRAPHICS RESOURCES BECOME A CRYPTO CHARITY DONATING CRYPTO LEVERAGING AI AT YOUR NONPROFIT ABOUT US WHO WE ARE TRANSPARENCY AFFILIATE PARTNERSHIPS CONTACT SUPPORT US Open Menu Close Menu Open Menu Close Menu BLOG CATEGORIES DAOs EDUCATION ENVIRONMENT REFI EQUITY INCLUSION FINANCIAL INCLUSION DEFI NFTs PHILANTHROPY SCIENCE DESCI SOCIAL IMPACT SUPPLY CHAIN COMMENTARY PODCASTS CRYPTO ALTRUISM PODCAST THE WEB3 NONPROFIT IMPACT ON OPTIMISM INFOGRAPHICS RESOURCES BECOME A CRYPTO CHARITY DONATING CRYPTO LEVERAGING AI AT YOUR NONPROFIT ABOUT US WHO WE ARE TRANSPARENCY AFFILIATE PARTNERSHIPS CONTACT SUPPORT US BLOG Folder CATEGORIES Back DAOs EDUCATION ENVIRONMENT REFI EQUITY INCLUSION FINANCIAL INCLUSION DEFI NFTs PHILANTHROPY SCIENCE DESCI SOCIAL IMPACT SUPPLY CHAIN COMMENTARY Folder PODCASTS Back CRYPTO ALTRUISM PODCAST THE WEB3 NONPROFIT IMPACT ON OPTIMISM INFOGRAPHICS Folder RESOURCES Back BECOME A CRYPTO CHARITY DONATING CRYPTO LEVERAGING AI AT YOUR NONPROFIT Folder ABOUT US Back WHO WE ARE TRANSPARENCY AFFILIATE PARTNERSHIPS CONTACT SUPPORT US 5 DeSci projects disrupting scientific research and development Project HighlightsScienceDAOs Mar 30 Written By Drew Simon 2021 was the year of decentralization and this momentum has only increased into 2022 Not only have we seen incredible growth in the decentralized finance DeFi space but we have also seen the emergence of social impact DAOs decentralized media platforms decentralized VC funds and more recently the emergence of a new field – Decentralized Science or DeSci In short “the decentralized science DeSci movement aims to harness new technologies such as blockchain and ‘Web3’ to address some important research pain points silos and bottlenecks” Whereas scientific research has long been viewed as overly bureaucratic and disjointed the DeSci movement aims to improve this by using blockchain to offer greater transparency and to take on the “profit hungry intermediaries” such as scientific journals that have dominated the traditional research spaceFor some resources on DeSci I recommend you check out the following articlesDeSci an opportunity to decentralize scientific research and publicationA Guide to DeSci the Latest Web3 MovementCall to join the decentralized science movementFor this blog post we will be highlighting 5 DeSci projects that are leading the way and positively disrupting scientific research and development1 VitaDAOOne of the best examples of DeSci in action is VitaDAO a Decentralized Autonomous Organization DAO focused on funding longevity research in “an open and democratic manner” Specifically they are focused on the decentralization of drug development focused on the extension of human life and healthspan They fund earlystage research with the goal of turning the research into biotech companiesVitaDAO is government by holders of VITA tokens which can either be purchased or earned through contributions of work or intellectual property With over 4000 members and 9M in funding raised to support scientific research VitaDAO has proven that the DeSci movement is no laughing matterCheck out some of their featured projects here2 SCINETThe SCINET platform which is built on blockchain enables retail and institutional investors to securely invest in scientific research and technology directly In addition to funding promising scientific research they also offer a “blockchainpowered” cloud laboratory for researchers a rigorous decentralized peer review process and enable researches to document their IP on an immutable blockchain3 AntidoteDAOAntidoteDAO is a decentralized community focused on funding cancer research and other cancer initiatives Their ecosystem includes a governance token and NFT collection which both enable individuals to vote on where to allocate funds In addition to providing funding to charities supporting cancer research and cancer patients a core focus of the DAO is on providing 100K seed fund grants to cancer research teams Research projects are first reviewed by the DAO’s Medical Advisory team and then put to the community for a vote Fun fact we have an upcoming podcast episode with AntidoteDAO that when available will be published HERE Crypto Altruism uses Ledger to keep its assets safeYou’ve probably heard the phrase “not your keys not your coins” By choosing a hard wallet like the Nano S Plus to store your crypto you can rest assured that the keys and the crypto are truly yoursGet your Ledger Nano S Plus now by clicking HERE or on the image below 4 LabDAOLabDAO is an emerging organization which is dedicated to operating a communityrun network of wet and dry labs with the goal of advancing scientific research and development A wet lab is one focused on analysing drugs chemicals and other biological matter whereas a dry lab is one focused on applied or computational mathematical analysis LabDAO is a relatively new project that is still in its infancy but has a promising mission and strong community of support around it 5 MoleculeMolecule is a decentralized scientific research funding platform that operates as a marketplace for researchers seeking out funding and individuals looking to invest in scientific research projects They are “connecting leading researchers to funding by turning intellectual property and its development into a liquid and easily investable asset”Researchers can list their research projects on the Molecule marketplace as a means to engage with potential investors and to secure funding for their project Molecule currently has over 250 research projects listed on their marketplace over 4500 DAO community members and 3 “Bio DAOs” with over 10M in funding in their network According to Molecule “The future of life science research will be driven by open liquid markets for intellectual property powered by web3 technology”We cover more amazing DeSci projects in our more recent postTen more DeSci projects disrupting scientific research development and knowledge sharing Buy me a coffee Send a tip in ETH cryptoaltruismethLike what you are reading Consider contributing to Crypto Altruism so we can continue putting out great content that shines a light on the good being done in the crypto and blockchain community SUPPORT CRYPTO ALTRUISM Please note we make use of affiliate marketing to provide readers with referrals to high quality and relevant products and services DeScidecentralizationscienceblockchainlists Drew Simon Previous Previous Crypto Altruism Podcast Episode 39 AntidoteDAO Decentralized funding of cancer research and charitable initiatives Next Next Crypto Altruism Podcast Episode 38 Using NFTs to empower content creators and help kids learn ft Susie Jaramillo CONTENTBLOGPODCASTINFOGRAPHICSCURATED LISTS ABOUTABOUTSUPPORT USCONTACTDISCLAIMERPRIVACY POLICY Buy me a coffee ETHERC20 cryptoaltruismeth 0xac5C0105914F3afb363699996C9914f193aeDD4A Sign up for our monthly newsletter Thank you © Crypto Altruism 2023 FOLLOW")
Training Details
Training Set Metrics
| Training set | Min | Median | Max |
|---|---|---|---|
| Word count | 20 | 2568.9241 | 13352 |
Training Hyperparameters
- batch_size: (8, 8)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.01
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: True
- warmup_proportion: 0.1
- l2_weight: 0.01
- seed: 42
- evaluation_strategy: steps
- eval_max_steps: -1
- load_best_model_at_end: True
Training Results
| Epoch | Step | Training Loss | Validation Loss |
|---|---|---|---|
| 0.0017 | 1 | 0.2236 | - |
| 0.0694 | 40 | - | 0.1379 |
| 0.0868 | 50 | 0.1722 | - |
| 0.1389 | 80 | - | 0.1440 |
| 0.1736 | 100 | 0.0536 | - |
| 0.2083 | 120 | - | 0.1412 |
| 0.2604 | 150 | 0.0293 | - |
| 0.2778 | 160 | - | 0.1343 |
| 0.3472 | 200 | 0.0234 | 0.1406 |
| 0.4167 | 240 | - | 0.1266 |
| 0.4340 | 250 | 0.0176 | - |
| 0.4861 | 280 | - | 0.1118 |
| 0.5208 | 300 | 0.0193 | - |
| 0.5556 | 320 | - | 0.1095 |
| 0.6076 | 350 | 0.0162 | - |
| 0.625 | 360 | - | 0.0926 |
| 0.6944 | 400 | 0.0223 | 0.0995 |
| 0.7639 | 440 | - | 0.0923 |
| 0.7812 | 450 | 0.018 | - |
| 0.8333 | 480 | - | 0.0814 |
| 0.8681 | 500 | 0.0045 | - |
| 0.9028 | 520 | - | 0.0801 |
| 0.9549 | 550 | 0.0074 | - |
| 0.9722 | 560 | - | 0.0794 |
Framework Versions
- Python: 3.11.12
- SetFit: 1.1.2
- Sentence Transformers: 3.4.1
- Transformers: 4.51.3
- PyTorch: 2.6.0+cu124
- Datasets: 3.5.1
- Tokenizers: 0.21.1
Citation
BibTeX
@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}