What the Near Future of Artificial Intelligence Could Be
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We will not develop AI systems to gradually adjust to difficult situations; rather, we will gradually turn difficult tasks into complex tasks.
“we will not develop AI systems in such a way that they will gradually adjust to difficult situations; rather, we will gradually turn difficult tasks into complex tasks.”
From ChatGPT, Education, and Understanding (2025) · cites this paper as Floridi 2019
Section 4 (page unavailable) says successful AI development will probably involve translating difficult tasks into complex ones by making environments AI-friendly. The citing sentence makes this a categorical prediction and rules out developing AI systems that adapt to difficult situations, whereas the source presents translation as one likely path, not the only one. (LLM, conf=0.86)
Experimental — accuracy not yet measuredAI systems thrive in complexity but fail miserably in difficulty.
“Now, AI systems thrive in the complexity, but they fail miserably in the difficulty.”
From ChatGPT, Education, and Understanding (2025) · cites this paper as Floridi 2019
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Artificial intelligence: a modern approach
Kumar, D. A., Balasubramanian, S., Byeon, D. H., & Manerkar, P. G. V. (1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 22,182 · see citing works
GAN（Generative Adversarial Nets）
淳司, 柴. (2017) · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · doi:10.3156/jsoft.29.5_177_2 · Cited by 19,268 · see citing works
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · cited 1× · see citing works
“…same counterfactual understanding of AI underpins the Turing test (Floridi et al. 2009), which, in this case, checks the ability of a machine to perform a task in such a way that the outcome would be indistinguishable from the outcome of a human agent working to achieve the same task (Turing 1950).”
ResultComputing Machinery and Intelligence (1950)
Turing, A. M. (2004) · doi:10.1093/oso/9780198250791.003.0017 · Cited by 6,120 · see citing works
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., et al. (2018) · Science · doi:10.1126/science.aar6404 · Cited by 3,562 · see citing works
Introduction to the Theory of Computation
Sipser, M. (1996) · ACM SIGACT News · doi:10.1145/230514.571645 · Cited by 2,828 · see citing works
Clinically applicable deep learning for diagnosis and referral in retinal disease
De Fauw, J., Ledsam, J. R., Romera-Paredes, B., Nikolov, S., Tomasev, N., Blackwell, S., Askham, H., Glorot, X., O’Donoghue, B., Visentin, D., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0107-6 · Cited by 2,639 · see citing works
Computational Complexity: A Modern Approach
Arora, S., & Barak, B. (2009) · Cited by 2,375 · see citing works
Computational Complexity: A Modern Approach
Arora, S., & Barak, B. (2009) · doi:10.1017/cbo9780511804090 · Cited by 1,690 · see citing works
Campbell, M., Hoane, A. J., & Hsu, F.-H. (2002) · Artificial Intelligence · doi:10.1016/s0004-3702(01)00129-1 · Cited by 1,226 · see citing works
On the Morality of Artificial Agents
Floridi, L., & Sanders, J. W. (2004) · Minds and Machines · doi:10.1023/b:mind.0000035461.63578.9d · Cited by 1,218 · see citing works
Self-citationThe Fourth Revolution: How the infosphere is reshaping human reality
Floridi, L. (2014) · International Linear Collider · Cited by 1,216 · see citing works
Self-citationEvaluation and accurate diagnoses of pediatric diseases using artificial intelligence
Liang, H., Tsui, B., Ni, H., Valentim, C. C. S., Baxter, S. L., Liu, G., Cai, W., Kermany, D., Sun, X., Chen, J., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0335-9 · Cited by 661 · see citing works
Floridi, L. (2010) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199641321.001.0001 · Cited by 644 · see citing works
Self-citationComputational Complexity: ADVANCED TOPICS
Arora, S., & Barak, B. (2009) · Cited by 578 · see citing works
Information: A Very Short Introduction
Floridi, L. (2010) · Cited by 558 · see citing works
Self-citationIntroduction to the Theory of Computation
Ina, I., Rachel, & Aarón (2013) · Cited by 497 · see citing works
Floridi, L. (2010) · Oxford University Press eBooks · doi:10.1093/actrade/9780199551378.001.0001 · Cited by 490 · see citing works
Self-citationClinical applications of machine learning algorithms: beyond the black box
Watson, D. S., Krutzinna, J., Bruce, I. N., Griffiths, C. E., McInnes, I. B., Barnes, M. R., & Floridi, L. (2019) · BMJ · doi:10.1136/bmj.l886 · Cited by 450 · see citing works
Self-citationRosenblueth, A., & Wiener, N. (1945) · Philosophy of Science · doi:10.1086/286874 · Cited by 377 · see citing works
(2013) · eYLS (Yale Law School) · Cited by 376 · see citing works
The Method of Levels of Abstraction
Floridi, L. (2008) · Minds and Machines · doi:10.1007/s11023-008-9113-7 · Cited by 356 · see citing works
Self-citationFloridi, L. (2019) · doi:10.1093/oso/9780198833635.001.0001 · Cited by 297 · see citing works
Self-citationBig Data and Their Epistemological Challenge
Floridi, L. (2012) · Philosophy & Technology · doi:10.1007/s13347-012-0093-4 · Cited by 217 · see citing works
Self-citationOpen Data, Data Protection, and Group Privacy
Floridi, L. (2014) · Philosophy & Technology · doi:10.1007/s13347-014-0157-8 · Cited by 178 · see citing works
Self-citationFloridi, L., Taddeo, M., & Turilli, M. (2008) · Minds and Machines · doi:10.1007/s11023-008-9130-6 · Cited by 117 · see citing works
Self-citationUnderstanding Epistemic Relevance
Floridi, L. (2007) · Erkenntnis · doi:10.1007/s10670-007-9087-5 · Cited by 102 · see citing works
Self-citationAI Knowledge Map: How to Classify AI Technologies
Corea, F. (2018) · Studies in big data · doi:10.1007/978-3-030-04468-8_4 · Cited by 82 · see citing works
Digital’s Cleaving Power and Its Consequences
Floridi, L. (2017) · Philosophy & Technology · doi:10.1007/s13347-017-0259-1 · Cited by 66 · see citing works
Self-citationSynthetic Data for Social GoodPreprint
Howe, B., Stoyanovich, J., Ping, H., Herman, B., & Gee, M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1710.08874 · Cited by 52 · see citing works
Corea, F. (2018) · Studies in big data · doi:10.1007/978-3-030-04468-8 · Cited by 44 · see citing works
Robotic ironing with 3D perception and force/torque feedback in household environments
Estevez, D., Victores, J. G., Fernandez-Fernandez, R., & Balaguer, C. (2017) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2017.8206556 · Cited by 37 · see citing works
Technoscience and Ethics Foresight
Floridi, L. (2014) · Philosophy & Technology · doi:10.1007/s13347-014-0180-9 · Cited by 35 · see citing works
Self-citationWhat a maker’s knowledge could be
Floridi, L. (2016) · Synthese · doi:10.1007/s11229-016-1232-8 · Cited by 20 · see citing works
Self-citationAllo, P. (2016) · VUBIR (Vrije Universiteit Brussel) · doi:10.4324/9781315757544.ch08 · Cited by 6 · see citing works
Kulas, J., Roji, R. G. P. P., & Smith, A. (2021) · doi:10.1002/9781119417453.ch3 · Cited by 5 · see citing works
Flagged first, then by citations
3 of the 39 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Campbell, M., Joseph Hoane, A., Jr., & Hsu, F.-h. J. (2002). Deep blue. Artificial Intelligence, 134(1-2), 57- 83.
- Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. Advances in Neural Information Processing Systems.
- McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Magazine, 27(4), 12.
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Reflexões sobre o futuro da inteligência artificial
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Sánchez-Reina, J. R., Theophilou, E., Hernández‐Leo, D., & Ognibene, D. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-67351-1_26 · Cited by 5 · see citing works
Deciphering intelligence analysis: the synthetic nature of the core intelligence function
Pili, G. (2022) · Intelligence & National Security · doi:10.1080/02684527.2022.2041947 · Cited by 4 · see citing works
The Impact of Open Data Standardization on the Successful Management of e-Government
Hyseni, B., & Bexheti, L. A. (2023) · Mediterranean Conference on Embedded Computing (MECO) · doi:10.1109/meco58584.2023.10154925 · Cited by 4 · see citing works
Floridi, L. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198883098.003.0002 · Cited by 5 · see citing works
Self-citationAI and Its New Winter: From Myths to Realities
Floridi, L. (2021) · Digital ethics lab yearbook · doi:10.1007/978-3-030-80083-3_6 · Cited by 4 · see citing works
Self-citationSimulation vs. Understanding: A Tension, in Quantum Chemistry and Beyond. Part A. Stage Setting
Hoffmann, R., & Malrieu, J. (2019) · Angewandte Chemie · doi:10.1002/ange.201902527 · Cited by 4 · see citing works
Battineni, G., Chintalapudi, N., Ricci, G., Ruocco, C., & Amenta, F. (2023) · doi:10.2196/preprints.53870 · Cited by 4 · see citing works
Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic
de Sá, Â. A. R., Carvalho, J. D., & Naves, E. L. M. (2021) · AI & Society · doi:10.1007/s00146-021-01315-9 · Cited by 3 · see citing works
(2020) · Research in ethical issues in organizations · doi:10.1108/s1529-209620200000023003 · Cited by 3 · see citing works
La IA y la ética digital: reales posibilidades y cuestionamientos para América Latina
Mont, C. G. (2023) · Comunicación · doi:10.18566/comunica.n49.a01 · Cited by 3 · see citing works
Floridi, L. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198883098.003.0005 · Cited by 2 · see citing works
Self-citationArtificial intelligence and the ethics of tomorrow
Wyk, V., & Holmner, M. (2024) · Proceedings of the International Conference on AI Research. · doi:10.34190/icair.5.1.3017 · Cited by 2 · see citing works
The Quantum Ecology as an Onto-Epistemological Framework: Toward an Ecological Theory of Sensing
Calzati, S., & Kerckhove, D. C. F. D. (2025) · Digital Society · doi:10.1007/s44206-025-00228-0 · Cited by 2 · see citing works
The Digital Present and the Future of Political Communication: Introduction and Prospects
Musiał-Karg, M., & Luengo, Ó. G. (2023) · Studies in digital politics and governance · doi:10.1007/978-3-031-33716-1_1 · Cited by 2 · see citing works
Root values and root skills: a new model for intelligence education
Gaspard, J. J. S., & Pili, G. (2024) · Intelligence & National Security · doi:10.1080/02684527.2024.2390762 · Cited by 2 · see citing works
A proposal of envelope theorem on the mixed traffic of pedestrians and various mobilities
Zou, L., & Yai, T. (2022) · Asian Transport Studies · doi:10.1016/j.eastsj.2021.100050 · Cited by 2 · see citing works
Mazzi, F. (2023) · CSR, sustainability, ethics & governance · doi:10.1007/978-3-031-09245-9_13 · Cited by 2 · see citing works
Floridi, L. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198883098.003.0003 · Cited by 2 · see citing works
Self-citationAI and the UN Sustainable Development Goals
Floridi, L. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198883098.003.0012 · Cited by 2 · see citing works
Self-citationTowards Robotic Things in SocietyPreprint
Loke, S. W. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.10253 · Cited by 2 · see citing works
Piparo, C. (2023) · Zbornik radova Pravnog fakulteta Novi Sad · doi:10.5937/zrpfns57-47113 · Cited by 1 · see citing works
A Inteligência Artificial no jornalismo brasileiro: transformações no ecossistema midiático
Barbosa, C. D. L., & Caldas, M. D. G. C. (2025) · Caderno Pedagógico · doi:10.54033/cadpedv22n7-183 · Cited by 1 · see citing works
Redrawing the labour blueprint: PRISMA insights on AI in the construction industry
Day, B., Gharehbaghi, K., Farnes, K., & Tee, K. F. (2025) · Infrastructure Asset Management · doi:10.1680/jinam.24.00058 · Cited by 1 · see citing works
- Authors
- Floridi, L.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Floridi, Luciano
- ORCID
- Floridi, Luciano
- Venue
- Philosophy & Technology
- Published
- 2019-03
- Volume
- 32
- Issue
- 1
- Pages
- 1-15
- ISSN
- 2210-5433 (ISSN-L)
- 2210-5441
- OpenAlex
- W2925023100
- Cited by
- 191
- References
- 39
- Citations by year
- 2026: 17 · 2025: 19 · 2024: 22 · 2023: 43 · 2022: 15 · 2021: 24 · 2020: 37 · 2019: 13 · 2016: 1
- FWCI
- 38.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Philosophy & Technology (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Keywords
- artificial intelligence, future of AI, artificial intelligence forecasting, AI regulation, EU AI policy, dystopian scenarios, AI risks, AI ethics
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