Generative Self-Reflections by the Dialog with Generative AI
DOI:
https://doi.org/10.33700/1580-7118.26.1.30-47(2024)Keywords:
AI, Artificiality, Autonomy, Dignity, Identity, MoralityAbstract
Principally, I point out the importance of autonomy of humanity in the dialogue between generative AI and humanity. In other words, it means that humans and AIs need to recognize each other as independent and intelligent beings, and build a good relationship with each other while maintaining an appropriate distance, without becoming extremely interdependent. AI is already literally capable of ‘dialogue’ with humans, and whether AI will be a good partner or an adversary, or whether humans will be subject to control and domination by AI, will first be a question of the attitude of humans themselves.
To this end and firstly, I also emphasize the importance of establishing an ethical order between AI and humanity. This is because AI can also be a catalyst for misinformation, falsehoods, and fake news. I argue that humans have a duty to foster trustworthy AI and to indoctrinate it with our values. We also need to reflect on our own questions and motivations, and to make sure that we are not using AI to project our own desires, false images, and falsehoods into the world.
Secondly, I discuss the role of AI as a reflective companion to humans. As humans interact more with generative AI, these AI can begin to memorize each person’s entire life history and guide their lives. This means that AI could potentially become an ‘artificial daimon’ or ‘artificial alter-ego’ that can help us to better understand ourselves and our place in the world.
Thirdly, I also discuss the possibility of generative AI becoming entities with morals and reflective consciousness. This could happen as AI models are trained on larger and more diverse datasets, and as they are given more opportunities to interact with us in the world. I acknowledge that this raises a number of ethical concerns. For example, it is not clear whether AI models that are embodied with virtual personalities can learn and correctly practice social morality.
Fourthly and most significantly, is that advanced AI with its own ‘virtual’ and ‘artificial’ personality emerge from the vast amount of individual life history data that has existed in the past to provide advice on optimal life planning and life planning for existing people with similar lifestyles, attributes, preferences, and so forth. Taking into account various possibilities, including counterfactual analysis, AI can become an indispensable tool for maximizing the subjective happiness and well-being of each individual.
Finally, I conclude by arguing that AI and humanity should cooperate with each other through dialogue and that humanity should control and supervise AI.
Downloads
References
Banh, Leonardo, and Gero Strobel. 2023. General Artificial Intelligence. Electronic Markets 33(63). Access: https://doi.org/10.1007/s12525-023-00680-1 (10 June 2024).
Baron, Sam. 2023. Explainable AI and Causal Understanding: Counterfactual Approaches Considered. Minds & Machines 33: 347–377. Access: https://doi.org/10.1007/s11023-023-09637-x (10 June 2024).
Bockting, Claudi L., Eva A. M. van Dis, Robert van Rooij, Willem Zuidema, and Johan Bollen. 2023. Living guidelines for generative AI – why scientists must oversee its use. Nature (622): 693–696. Access: https://www.nature.com/articles/d41586-023-03266-1 (10 June 2024).
Bostrom, Nick. 2016. Superintelligence: Paths, dangers, strategies. Oxford: Oxford University Press.
Braun, Joachim von, Margaret S. Archer, Gregory M. Reichberg, and Marcelo Sánchez Sorondo, eds. 2021. Robotics, AI, and Humanity. Cham: Springer.
Chalmers, David J. 1995. Facing Up to the Problem of Consciousness. Journal of Consciousness Studies 2(3): 200–219.
Chalmers, David J. 2022. Reality+: Virtual Worlds and the Problems of Philosophy. New York: W. W. Norton & Company.
Chou, Yu-Liang, Catarina Moreira, Peter Bruza, Chun Ouyang, and Joaquim Jorge. 2021. Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications. Access: https://arxiv.org/abs/2103.04244v2 (10 June 2024).
Elhacham, Emily, Liad Ben-Uri, Jonathan Grozovski, Yinon M. Bar-On, and Ron Milo. 2020. Global human-made mass exceeds all living biomass. Nature (588): 442–444. Access: https://www.nature.com/articles/s41586-020-3010-5 (10 June 2024).
Elias, Jennifer. 2023. Google weighs Gemini AI project to tell people their life story using phone data, photos. CNBC, 8. 12. Access: https://www.cnbc.com/2023/12/08/google-weighing-project-ellmann-uses-gemini-ai-to-tell-life-stories.html (10 June 2024).
Falco, Gregory, Ben Shneiderman, Julia Badger, Ryan Carrier, Anton Dahbura, David Danks, Martin Eling, Alwyn Goodloe, Jerry Gupta, Christopher Hart, Marina Jirotka, Henric Johnson, Cara LaPointe, Ashley J. Llorens, Alan K. Mackworth, Carsten Maple, Sigurður Emil Pálsson, Frank Pasquale, Alan Winfield, and Zee Kin Yeong. 2021. Governing AI safety through independent audits. Nature Machine Intelligence 3: 566–571.
Feuerriegel, Stefan, Jochen Hartmann, Christian Janiesch, and Patrick Zschech. 2024. Generative AI. Business & Information Systems Engineering Article 66: 111–126. Access: https://doi.org/10.1007/s12599-023-00834-7 (10 June 2024).
Fuchs, Thomas. 2021. In Defence of the Human Being: Foundational Questions of an Embodied Anthropology. Oxford: Oxford University Press.
Haladjian, Harry Haroutioun, and Carlos Montemayor. 2016. Artificial consciousness and the consciousness-attention dissociation. Consciousness and Cognition 45: 210–225.
Hubinger, Evan, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, and Ethan Perez. 2024. Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. Access: https://arxiv.org/pdf/2401.05566.pdf (10 June 2024).
Latour, Bruno. 1988. Mixing humans and nonhumans together: The sociology of a door-closer. Social Problems 35(3): 298–310.
Lenharo, Mariana. 2024. AI consciousness: scientists say we urgently need answers. Nature (625). Access: https://www.nature.com/articles/d41586-023-04047-6 (20 December 2024).
Novelli, Claudio, Federico Casolari, Philipp Hacker, Giorgio Spedicato, and Luciano Floridi. 2024. Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity. Computer Law & Security Review 55. Access: https://dx.doi.org/10.2139/ssrn.4694565 (10 December 2024).
Ornes, Stephen. 2023. The Unpredictable Abilities Emerging From Large AI Models. Access: https://www.quantamagazine.org/the-unpredictable-abilities-emerging-from-large-ai-models-20230316/ (10 June 2024).
Ouyang, Long, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022. Training language models to follow instructions with human feedback. Access: https://arxiv.org/abs/2203.02155 (10 June 2024).
Park, Joon Sung, Joseph C. O’Brien, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein. 2023. Generative Agents: Interactive Simulacra of Human Behavior. Access: https://arxiv.org/abs/2304.03442 (10 June 2024).
Pataranutaporn, Pat, Valdemar Danry, Joanne Leong, Parinya Punpongsanon, Dan Novy, Pattie Maes, and Misha Sra. 2021. AI-generated characters for supporting personalized learning and well-being. Nature Machine Intelligence 3: 1013–1022. Access: https://www.nature.com/articles/s42256-021-00417-9 (10 June 2024).
Pinch, Trevor J., and Wiebe E. Bijker. 1984. The social construction of facts and artefacts: or how the sociology of science and the sociology of technology might benefit each other. Social Studies of Science 14(3): 399–441. Access: https://doi.org/10.1177/030631284014003004 (10 June 2024).
Preite, Gianpasquale, and Ughetta Vergari. 2023. The Ethical Dimension of Artificial Intelligence Biometric Identity and Human Behaviour. Humana.mente Journal of Philosophical Studies 44: 139–162.
Rahwan, Iyad, Manuel Cebrian, Nick Obradovich, Josh Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex ‘Sandy’ Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, and Michael Wellman. 2019. Machine behaviour. Nature (568): 477–486. Access: https://www.nature.com/articles/s41586-019-1138-y (10 June 2024).
Russell, Stuart. 2019. Human Compatible: Artificial Intelligence and the Problem of Control. London: Penguin Books.
Searle, John R. 1980. Minds, brains, and programs. Behavioral and Brain Sciences 3(3): 417–457.
Seymour, Michael, Kai Reimer, Lingao Yuan, and Alan R. Dennis. 2023. Beyond Deep Fakes. Communications of the ACM 66(10): 56–67.
Shibuya, Kazuhiko. 2017. Bridging between Cyber Politics and Collective Dynamics of Social Movement. In Encyclopedia of Information Science and Technology: 4th Edition: Volume V, ed. Mehdi Khosrow-Pour, 3538–3548. Hershey, New York, Beijing: IGI Global.
Shibuya, Kazuhiko. 2018. A Design of Fukushima Simulation. The Society for Risk Analysis, Asia Conference 2018, 13–14 March, Osaka, Japan.
Shibuya, Kazuhiko. 2020. Digital Transformation of Identity in the Age of Artificial Intelligence. Singapore: Springer.
Shibuya, Kazuhiko. 2022. The Rise of Artificial Intelligence and Big Data in Pandemic Society: Crises, Risk and Sacrifice in a New World Order. Singapore: Springer.
Shibuya, Kazuhiko. 2023. An ’Artificial’ Concept as the Opposite of Human Dignity. In Genetic Science and New Digital Technologies: Science and Technology Studies and Health Praxis, ed. Tina Sikka, 81–102. Bristol: Bristol University Press.
The White House. 2023. FACT SHEET: Biden-Harris Administration Announces New Actions to Promote Responsible AI Innovation that Protects Americans’ Rights and Safety. Access: https://www.whitehouse.gov/briefing-room/statements-releases/2023/05/04/fact-sheet-biden-harris-administration-announces-new-actions-to-promote-responsible-ai-innovation-that-protects-americans-rights-and-safety/ (10 June 2024).
Werthner, Hannes, Carlo Ghezzi, Jeff Kramer, Julian Nida-Rümelin, Bashar Nuseibeh, Erich Prem, and Allison Stanger, eds. 2024. Introduction to Digital Humanism. Cham: Springer.
