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, a paper proposed to use blockchain (distributed ledger technology) to promote "transparency, verifiability, and decentralization in AI development and usage".[157] Audio deepfakes [edit]Instances of users abusing software to generate controversial statements in the vocal style of celebrities, public officials, and other famous individuals have raised ethical concerns over voice generation AI.[158][159][160][161][162][163] In response, companies such as ElevenLabs have stated that they would wo
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such as ElevenLabs have stated that they would work on mitigating potential abuse through safeguards and identity verification.[164] Concerns and fandoms have spawned from AI-generated music. The same software used to clone voices has been used on famous musicians' voices to create songs that mimic their voices, gaining both tremendous popularity and criticism.[165][166][167] Similar techniques have also been used to create improved quality or full-length versions of songs that have been leaked
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ull-length versions of songs that have been leaked or have yet to be released.[168] Generative AI has also been used to create new digital artist personalities, with some of these receiving enough attention to receive record deals at major labels.[169] The developers of these virtual artists have also faced their fair share of criticism for their personified programs, including backlash for "dehumanizing" an artform, and also creating artists which create unrealistic or immoral appeals to their
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ch create unrealistic or immoral appeals to their audiences.[170] Illegal imagery [edit]Many websites that allow explicit AI generated images or videos have been created,[171] and this has been used to create illegal content, such as rape, child sexual abuse material,[172][173] necrophilia, and zoophilia. Cybercrime [edit]Generative AI's ability to create realistic fake content has been exploited in numerous types of cybercrime, including phishing scams.[174] Deepfake video and audio have been u
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g scams.[174] Deepfake video and audio have been used to create disinformation and fraud. In 2020, former Google click fraud czar Shuman Ghosemajumder argued that once deepfake videos become perfectly realistic, they would stop appearing remarkable to viewers, potentially leading to uncritical acceptance of false information.[175] Additionally, large language models and other forms of text-generation AI have been used to create fake reviews of e-commerce websites to boost ratings.[176] Cybercrim
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commerce websites to boost ratings.[176] Cybercriminals have created large language models focused on fraud, including WormGPT and FraudGPT.[177] A 2023 study showed that generative AI can be vulnerable to jailbreaks, reverse psychology and prompt injection attacks, enabling attackers to obtain help with harmful requests, such as for crafting social engineering and phishing attacks.[178] Additionally, other researchers have demonstrated that open-source models can be fine-tuned to remove their s
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-source models can be fine-tuned to remove their safety restrictions at low cost.[179] Reliance on industry giants [edit]Training frontier AI models requires an enormous amount of computing power. Usually only Big Tech companies have the financial resources to make such investments. Smaller start-ups such as Cohere and OpenAI end up buying access to data centers from Google and Microsoft respectively.[180] Energy and environment [edit]AI has a significant carbon footprint due to growing energy c
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gnificant carbon footprint due to growing energy consumption from both training and usage.[130][131] Scientists and journalists have expressed concerns about the environmental impact that the development and deployment of generative models are having: high CO2 emissions,[181][182][183] large amounts of freshwater used for data centers,[184][185] and high amounts of electricity usage.[182][186][187] There is also concern that these impacts may increase as these models are incorporated into widely
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rease as these models are incorporated into widely used search engines such as Google Search and Bing,[186] as chatbots and other applications become more popular,[185][186] and as models need to be retrained.[186] The carbon footprint of generative AI globally is estimated to be growing steadily, with potential annual emissions ranging from 18.21 to 245.94 million tons of CO2 by 2035,[188] with the highest estimates for 2035 nearing the impact of the United States beef industry on emissions (cu
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f the United States beef industry on emissions (currently estimated to emit 257.5 million tons annually as of 2024).[189] Proposed mitigation strategies include factoring potential environmental costs prior to model development or data collection,[181] increasing efficiency of data centers to reduce electricity/energy usage,[183][186][187] building more efficient machine learning models,[182][184][185] minimizing the number of times that models need to be retrained,[183] developing a government-
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eed to be retrained,[183] developing a government-directed framework for auditing the environmental impact of these models,[183][184] regulating for transparency of these models,[183] regulating their energy and water usage,[184] encouraging researchers to publish data on their models' carbon footprint,[183][186] and increasing the number of subject matter experts who understand both machine learning and climate science.[183] Content quality [edit]The New York Times defines slop as analogous to
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t]The New York Times defines slop as analogous to spam: "shoddy or unwanted A.I. content in social media, art, books and ... in search results."[190] Journalists have expressed concerns about the scale of low-quality generated content with respect to social media content moderation,[191] the monetary incentives from social media companies to spread such content,[191][192] false political messaging,[192] spamming of scientific research paper submissions,[193] increased time and effort to find hig
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ssions,[193] increased time and effort to find higher quality or desired content on the Internet,[194] the indexing of generated content by search engines,[195] and on journalism itself.[196] A paper published by researchers at Amazon Web Services AI Labs found that over 57% of sentences from a sample of over 6 billion sentences from Common Crawl, a snapshot of web pages, were machine translated. Many of these automated translations were seen as lower quality, especially for sentences that were
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lower quality, especially for sentences that were translated across at least three languages. Many lower-resource languages (ex. Wolof, Xhosa) were translated across more languages than higher-resource languages (ex. English, French).[197][198] In September 2024, Robyn Speer, the author of wordfreq, an open source database that calculated word frequencies based on text from the Internet, announced that she had stopped updating the data for several reasons: high costs for obtaining data from Redd
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l reasons: high costs for obtaining data from Reddit and Twitter, excessive focus on generative AI compared to other methods in the natural language processing community, and that "generative AI has polluted the data".[199] The adoption of generative AI tools led to an explosion of AI-generated content across multiple domains. A study from University College London estimated that in 2023, more than 60,000 scholarly articles—over 1% of all publications—were likely written with LLM assistance.[200
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tions—were likely written with LLM assistance.[200] According to Stanford University's Institute for Human-Centered AI, approximately 17.5% of newly published computer science papers and 16.9% of peer review text now incorporate content generated by LLMs.[201] Many academic disciplines have concerns about the factual reliably of academic content generated by AI.[202] Visual content follows a similar trend. Since the launch of DALL-E 2 in 2022, it is estimated that an average of 34 million images
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is estimated that an average of 34 million images have been created daily. As of August 2023, more than 15 billion images had been generated using text-to-image algorithms, with 80% of these created by models based on Stable Diffusion.[203] If AI-generated content is included in new data crawls from the Internet for additional training of AI models, defects in the resulting models may occur.[204] Training an AI model exclusively on the output of another AI model produces a lower-quality model.
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another AI model produces a lower-quality model. Repeating this process, where each new model is trained on the previous model's output, leads to progressive degradation and eventually results in a "model collapse" after multiple iterations.[205] Tests have been conducted with pattern recognition of handwritten letters and with pictures of human faces.[206] As a consequence, the value of data collected from genuine human interactions with systems may become increasingly valuable in the presence
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s may become increasingly valuable in the presence of LLM-generated content in data crawled from the Internet. On the other side, synthetic data is often used as an alternative to data produced by real-world events. Such data can be deployed to validate mathematical models and to train machine learning models while preserving user privacy,[207] including for structured data.[208] The approach is not limited to text generation; image generation has been employed to train computer vision models.[2
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s been employed to train computer vision models.[209] Misuse in journalism [edit]In January 2023, Futurism.com broke the story that CNET had been using an undisclosed internal AI tool to write at least 77 of its stories; after the news broke, CNET posted corrections to 41 of the stories.[210] In April 2023, the German tabloid Die Aktuelle published a fake AI-generated interview with former racing driver Michael Schumacher, who had not made any public appearances since 2013 after sustaining a bra
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blic appearances since 2013 after sustaining a brain injury in a skiing accident. The story included two possible disclosures: the cover included the line "deceptively real", and the interview included an acknowledgment at the end that it was AI-generated. The editor-in-chief was fired shortly thereafter amid the controversy.[211] Other outlets that have published articles whose content or byline have been confirmed or suspected to be created by generative AI models – often with false content, e
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generative AI models – often with false content, errors, or non-disclosure of generative AI use – include: - NewsBreak[212][213] - outlets owned by Arena Group - B&H Photo[216] - outlets owned by Gannett - The Columbus Dispatch[217][218] - Reviewed[219] - USA Today[220] - Journal Star[221] - El Paso Times[221] - Fort Collins Coloradoan[221] - The Record[221] - The Augusta Chronicle[221] - The Providence Journal[221] - Argus Leader[221] - Southwest Times Record[221] - The Des Moines Register[221]
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t Times Record[221] - The Des Moines Register[221] - North Jersey Media Group[221] - Pocono Record[221] - MSN[222] - News Corp[223] - outlets owned by G/O Media[224] - The Irish Times[229] - outlets owned by Red Ventures - BuzzFeed[231] - Newsweek[232] - Hoodline[233][234][235] - outlets owned by Outside Inc. - Hollywood Life[220] - Us Weekly[220] - The Los Angeles Times[220] - Cody Enterprise[236] - Cosmos[237] - outlets owned by McClatchy - outlets owned by Ziff Davis - outlets owned by Hearst
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lets owned by Ziff Davis - outlets owned by Hearst - outlets owned by IAC Inc. - outlets owned by Street Media - Riverfront Times[239] - Apple Intelligence[240] In May 2024, Futurism noted that a content management system video by AdVon Commerce, who had used generative AI to produce articles for many of the aforementioned outlets, appeared to show that they "had produced tens of thousands of articles for more than 150 publishers."[220] News broadcasters in Kuwait, Greece, South Korea, India, Ch
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dcasters in Kuwait, Greece, South Korea, India, China and Taiwan have presented news with anchors based on Generative AI models, prompting concerns about job losses for human anchors and audience trust in news that has historically been influenced by parasocial relationships with broadcasters, content creators or social media influencers.[241][242][243] Algorithmically generated anchors have also been used by allies of ISIS for their broadcasts.[244] In 2023, Google reportedly pitched a tool to
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244] In 2023, Google reportedly pitched a tool to news outlets that claimed to "produce news stories" based on input data provided, such as "details of current events". Some news company executives who viewed the pitch described it as "[taking] for granted the effort that went into producing accurate and artful news stories."[245] In February 2024, Google launched a program to pay small publishers to write three articles per day using a beta generative AI model. The program does not require the
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rative AI model. The program does not require the knowledge or consent of the websites that the publishers are using as sources, nor does it require the published articles to be labeled as being created or assisted by these models.[246] Many defunct news sites (The Hairpin, The Frisky, Apple Daily, Ashland Daily Tidings, Clayton County Register, Southwest Journal) and blogs (The Unofficial Apple Weblog, iLounge) have undergone cybersquatting, with articles created by generative AI.[247][248][249
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h articles created by generative AI.[247][248][249][250][251][252][253][254] United States Senators Richard Blumenthal and Amy Klobuchar have expressed concern that generative AI could have a harmful impact on local news.[255] In July 2023, OpenAI partnered with the American Journalism Project to fund local news outlets for experimenting with generative AI, with Axios noting the possibility of generative AI companies creating a dependency for these news outlets.[256] Meta AI, a chatbot based on
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se news outlets.[256] Meta AI, a chatbot based on Llama 3 which summarizes news stories, was noted by The Washington Post to copy sentences from those stories without direct attribution and to potentially further decrease the traffic of online news outlets.[257] In response to potential pitfalls around the use and misuse of generative AI in journalism and worries about declining audience trust, outlets around the world, including publications such as Wired, Associated Press, The Quint, Rappler o
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h as Wired, Associated Press, The Quint, Rappler or The Guardian have published guidelines around how they plan to use and not use AI and generative AI in their work.[258][259][260][261] In June 2024, Reuters Institute published their Digital News Report for 2024. In a survey of people in America and Europe, Reuters Institute reports that 52% and 47% respectively are uncomfortable with news produced by "mostly AI with some human oversight", and 23% and 15% respectively report being comfortable.
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3% and 15% respectively report being comfortable. 42% of Americans and 33% of Europeans reported that they were comfortable with news produced by "mainly human with some help from AI". The results of global surveys reported that people were more uncomfortable with news topics including politics (46%), crime (43%), and local news (37%) produced by AI than other news topics.[262] See also [edit]- Artificial general intelligence – Type of AI with wide-ranging abilities - Artificial imagination – Ar
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de-ranging abilities - Artificial imagination – Artificial simulation of human imagination - Artificial intelligence art – Visual media created with AI - Artificial life – Field of study - Chatbot – Program that simulates conversation - Computational creativity – Multidisciplinary endeavour - Generative adversarial network – Deep learning method - Generative pre-trained transformer – Type of large language model - Large language model – Type of machine learning model - Music and artificial intel
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achine learning model - Music and artificial intelligence – Usage of artificial intelligence to generate music - Generative AI pornography – Explicit material produced by generative AI - Procedural generation – Method in which data is created algorithmically as opposed to manually - Retrieval-augmented generation – Type of information retrieval using LLMs - Stochastic parrot – Term used in machine learning References [edit]- ^ Newsom, Gavin; Weber, Shirley N. (September 5, 2023). "Executive Orde
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r, Shirley N. (September 5, 2023). "Executive Order N-12-23" (PDF). Executive Department, State of California. Archived (PDF) from the original on February 21, 2024. Retrieved September 7, 2023. - ^ Pinaya, Walter H. L.; Graham, Mark S.; Kerfoot, Eric; Tudosiu, Petru-Daniel; Dafflon, Jessica; Fernandez, Virginia; Sanchez, Pedro; Wolleb, Julia; da Costa, Pedro F.; Patel, Ashay (2023). "Generative AI for Medical Imaging: extending the MONAI Framework". arXiv:2307.15208 [eess.IV]. - ^ "What is Chat
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rk". arXiv:2307.15208 [eess.IV]. - ^ "What is ChatGPT, DALL-E, and generative AI?". McKinsey. Archived from the original on April 23, 2023. Retrieved December 14, 2024. - ^ "What is generative AI?". IBM. March 22, 2024. Archived from the original on December 13, 2024. Retrieved December 13, 2024. - ^ Pasick, Adam (March 27, 2023). "Artificial Intelligence Glossary: Neural Networks and Other Terms Explained". The New York Times. ISSN 0362-4331. Archived from the original on September 1, 2023. Ret
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chived from the original on September 1, 2023. Retrieved April 22, 2023. - ^ Karpathy, Andrej; Abbeel, Pieter; Brockman, Greg; Chen, Peter; Cheung, Vicki; Duan, Yan; Goodfellow, Ian; Kingma, Durk; Ho, Jonathan; Rein Houthooft; Tim Salimans; John Schulman; Ilya Sutskever; Wojciech Zaremba (June 16, 2016). "Generative models". OpenAI. Archived from the original on November 17, 2023. Retrieved March 15, 2023. - ^ a b Griffith, Erin; Metz, Cade (January 27, 2023). "Anthropic Said to Be Closing In on
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ary 27, 2023). "Anthropic Said to Be Closing In on $300 Million in New A.I. Funding". The New York Times. Archived from the original on December 9, 2023. Retrieved March 14, 2023. - ^ Lanxon, Nate; Bass, Dina; Davalos, Jackie (March 10, 2023). "A Cheat Sheet to AI Buzzwords and Their Meanings". Bloomberg News. Archived from the original on November 17, 2023. Retrieved March 14, 2023. - ^ Metz, Cade (March 14, 2023). "OpenAI Plans to Up the Ante in Tech's A.I. Race". The New York Times. ISSN 0362
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n Tech's A.I. Race". The New York Times. ISSN 0362-4331. Archived from the original on March 31, 2023. Retrieved March 31, 2023. - ^ Thoppilan, Romal; De Freitas, Daniel; Hall, Jamie; Shazeer, Noam; Kulshreshtha, Apoorv (January 20, 2022). "LaMDA: Language Models for Dialog Applications". arXiv:2201.08239 [cs.CL]. - ^ Roose, Kevin (October 21, 2022). "A Coming-Out Party for Generative A.I., Silicon Valley's New Craze". The New York Times. Archived from the original on February 15, 2023. Retrieve
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e; Gokturk, Burak (March 14, 2023). "Google Cloud brings generative AI to developers, businesses, and governments". Archived from the original on November 17, 2023. Retrieved March 15, 2023. - ^ Simon, Felix M.; Altay, Sacha; Mercier, Hugo (October 18, 2023). "Misinformation reloaded? Fears about the impact of generative AI on misinformation are overblown" (PDF). Harvard Kennedy School Misinformation Review. doi:10.37016/mr-2020-127. S2CID 264113883. Retrieved November 16, 2023. - ^ Hendrix, Jus
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883. Retrieved November 16, 2023. - ^ Hendrix, Justin (May 16, 2023). "Transcript: Senate Judiciary Subcommittee Hearing on Oversight of AI". techpolicy.press. Archived from the original on November 17, 2023. Retrieved May 19, 2023. - ^ "New AI systems collide with copyright law". BBC News. August 1, 2023. Retrieved September 28, 2024. - ^ "The Transformative Impact of Generative AI on Software Development and Quality Engineering". Unite.AI. July 17, 2024. Archived from the original on April 10,
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17, 2024. Archived from the original on April 10, 2025. Retrieved April 10, 2025. - ^ Raza, Marium M.; Venkatesh, Kaushik P.; Kvedar, Joseph C. (March 7, 2024). "Generative AI and large language models in health care: pathways to implementation". npj Digital Medicine. 7 (1): 1–3. doi:10.1038/s41746-023-00988-4. ISSN 2398-6352. PMC 10920625. - ^ Mogaji, Emmanuel (January 7, 2025). "How generative AI is transforming financial services – and what it means for customers". The Conversation. Retrieve
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t means for customers". The Conversation. Retrieved April 10, 2025. - ^ Bean, Thomas H. Davenport and Randy (June 19, 2023). "The Impact of Generative AI on Hollywood and Entertainment". MIT Sloan Management Review. Archived from the original on August 6, 2024. Retrieved April 10, 2025. - ^ Brynjolfsson, Erik; Li, Danielle; Raymond, Lindsey R. (April 2023), Generative AI at Work (Working Paper), Working Paper Series, doi:10.3386/w31161, archived from the original on March 28, 2024, retrieved Jan
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from the original on March 28, 2024, retrieved January 21, 2024 - ^ "Don't fear an AI-induced jobs apocalypse just yet". The Economist. March 6, 2023. Archived from the original on November 17, 2023. Retrieved March 14, 2023. - ^ Coyle, Jake (September 27, 2023). "In Hollywood writers' battle against AI, humans win (for now)". AP News. Associated Press. Archived from the original on April 3, 2024. Retrieved January 26, 2024. - ^ Harreis, H.; Koullias, T.; Roberts, Roger. "Generative AI: Unlockin
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lias, T.; Roberts, Roger. "Generative AI: Unlocking the future of fashion". Archived from the original on November 17, 2023. Retrieved March 14, 2023. - ^ "How Generative AI Can Augment Human Creativity". Harvard Business Review. June 16, 2023. ISSN 0017-8012. Archived from the original on June 20, 2023. Retrieved June 20, 2023. - ^ Grinstead, Charles Miller; Snell, James Laurie (1997). Introduction to Probability. American Mathematical Society. pp. 464–466. ISBN 978-0-8218-0749-1. - ^ Bremaud,
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Bekey, George A. (ed.). An Autonomous Spacecraft Agent Prototype. Autonomous Robots Volume 5, No. 1. pp. 29–45. Our deliberator is a traditional generative AI planner based on the HSTS planning framework (Muscettola, 1994), and our control component is a traditional spacecraft attitude control system (Hackney et al. 1993). We also add an architectural component explicitly dedicated to world modeling (the mode identifier), and distinguish between control and monitoring. - ^ Jebara, Tony (2012).
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trieved October 6, 2024. - ^ Chandraseta, Rionaldi (January 21, 2021). "Generate Your Favourite Characters' Voice Lines using Machine Learning". Towards Data Science. Archived from the original on January 21, 2021. Retrieved December 18, 2024. - ^ Temitope, Yusuf (December 10, 2024). "15.ai Creator reveals journey from MIT Project to internet phenomenon". The Guardian. Archived from the original on December 28, 2024. Retrieved December 25, 2024. - ^ Anirudh VK (March 18, 2023). "Deepfakes Are El
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- ^ Anirudh VK (March 18, 2023). "Deepfakes Are Elevating Meme Culture, But At What Cost?". Analytics India Magazine. Archived from the original on December 26, 2024. Retrieved December 18, 2024. While AI voice memes have been around in some form since '15.ai' launched in 2020, [...] - ^ Coldewey, Devin (January 5, 2021). "OpenAI's DALL-E creates plausible images of literally anything you ask it to". TechCrunch. Archived from the original on January 6, 2021. Retrieved March 15, 2023. - ^ "Stable
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