Book on the Evaluation of Natural and Artificial Intelligence, Cambridge University Press 2017,
Prose Award 2018 presented by the Association of American Publishers.
Follow our project "Paradigms of Artificial General Intelligence and Their Associated Risks", co-led with Seán Ó hÉigeartaigh at CSER, funded by Future of Life's AGI safety grants.
Follow our project "COST-OMIZE: Understanding Customer Behavior under Urban Segregation for Cost-reducing and Sustainable Logistics",
MIT International Science and Technology Initiatives INDITEX Fund, with A. Pentland (MIT), J. Balsa (MIT) and C. Ferri (VRAIN).
Follow our project "Healthcare and logistic solutions for COVID-19 based on DS/AI", funded by AVI, with partners at IIS-Hospital La Fe, ITI and UA. Some media coverage.
Recent Highlights
- Co-organising ECML/PKDD Workshop on Automating Data Science 2021.
- New papers accepted for Communications of the ACM ("Automating Data Science: Prospects and Challenges" with T. De Bie, L. De Raedt, H. H. Hoos, P. Smyth and C. K. I. Williams) and Journal of Artificial Intelligence Research ("Measuring the occupational impact of AI: tasks, cognitive abilities and AI benchmarks" with S. Tolan, A. Pesole, F. Martinez-Plumed, E. Fernandez-Macias and E. Gomez), 2021.
- Co-organising AISafety Workshop 2021.
- New papers accepted for Artificial Intelligence Journal ("Making sense of sensory input" with Richard Evans et al.), Machine Learning Journal ("AUTOMAT[R]IX: learning simple matrix pipelines"), J. of Intelligent Systems ("Missing the missing values: The ugly duckling of fairness in machine learning"), Nature Mat Intell ("Research Community Dynamics behind Popular AI Benchmarks") and Telematics and Informatics ("Futures of artificial intelligence through technology readiness levels") 2021.
- Invited for the Spanish Senate's Commission on Economic Affairs and Digital Transformation, March 2021.
- Paper "Negative Side Effects and AI Agent Indicators: Experiments in SafeLife" at SafeAI Workshop at AAAI 2021.
- Participated in the OECD Expert Meeting on Skills and Tests for Assessing AI and Robotics, with this presentation.
- New papers accepted for Minds and Machines ("Twenty Years Beyond the Turing Test: Moving Beyond the Human Judges Too") and Expert Systems and Applications ("Learning alternative ways of performing a task").
- Animal AI Olympics Paper: "The Animal-AI Testbed and Competition", Proceedings of Machine Learning Research, 2020.
- Co-organising the SafeAI Workshops at AAAI 2020 and AAAI 2021.
- Co-organised the at AISafety Workshops 2019 and 2020.
- Co-organised the 1st Workshop on Evaluating Progress in AI (EPAI2020) at ECAI 2020.
- Four papers accepted for ECAI 2020: "Tracking AI: The Capability is (Not) Near" with F. Martínez-Plumed and E. Gómez, "AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues" with F. Martínez-Plumed, Shahar Avin, Jess Whittlestone and Seán O h'Eigeartaigh, "Finite and Confident Teaching in Expectation:Sampling from Infinite Concept Classes" with J.A. Telle and "Family and Prejudice: A Behavioural Taxonomy of Machine Learning Techniques" with the DMIP team.
- Read our paper: CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories, IEEE Transactions on Knowledge and Data Engineering journal, 2020.
- Read our paper: "Does AI Qualify for the Job? A Bidirectional Model Mapping Labour and AI Intensities", AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, 2020.
- Read our paper:
The Teaching Size: Computable Teachers and Learners for Universal Languages" with Jan Arne Telle and Cèsar Ferri, Machine Learning Journal, 2019
- Co-organised the Animal-AI Olympics, 2019.
- Co-organised the ECMLPKDD workshop on Automating Data Science (AutoDS), 2019.
- Read: Journal of Artificial Intelligence Research: "AI Generality and Spearman's Law of Diminishing Returns", 2019.
- Contributing to the AI Safety Landscape.
- Gave a talk at the
Cambridge Science Festival, 2019.
- Measure for measure column: "Unbridled mental power", Nature Physics, vol. 15, 2019.
- Read our paper Item Response Theory in AI: Analysing Machine Learning Classifiers at the Instance Level", Artificial Intelligence Journal, 2019.
RESEARCH
One of the great scientific challenges of this century is to understand what intelligence is and how it can be recreated. My bit is, on one hand, the evaluation and measurement of intelligent systems in general and machine learning in particular and, on the other hand, some more applied research on data science, data mining and inductive programming. However, I'm interested in many other things, and my publication profiles below can give a better account of what my research really looks like:
Here you also have a selection of some recent tutorials and presentations:
- Identifying Artificial Intelligence Capabilieis: What and How to Test, OECD Expert Meeting on Skills and Tests for Assessing AI and Robotics, 5-6 October 2020.
- Measuring Intelligence Incrementally: Search, Demonstration and Transmission, DARPA Machine Common Sense PI Meeting, July 21-23, 2020.
- AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues, European Conference on Artificial Intelligence, Aug 29 - Sep 8, 2020.
- On Broken Yardsticks and Measurement Scales, (paper), MetaEval@AAAI2020, New York, Feb 8, 2020.
- Surveying Safety-Relevant AI Characteristics, SafeAI2019 AAAI Workshop, Honolulu, 27 January 2019.
- AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI, AAAI / ACM Conference on Artificial Intelligence, Ethics and Society, Honolulu, 27-28 January 2019.
- Artificial Intelligence : Present, Future and Beyond, [video], HUMAINT Winter school on AI and its ethical, social, legal and economic impact, JRC Seville, February 4-8th, 2019.
- The What and How of AI Evaluation, [video], HUMAINT Winter school on AI and its ethical, social, legal and economic impact, JRC Seville, February 4-8th, 2019.
- Artificial Intelligence and Data Science : Looking Ahead, Springer Nature Conference on Artificial Intelligence in Biomedicine, Madrid 7th February 2019.
- Diversity Unites Intelligence: Measuring Generality at Varieties of Minds 2018 in Cambridge, 2018
- Measuring A(G)I Right: Some Theoretical and Practical Considerations at DeepMind, London, 2018
- Natural and Artificial Intelligence: Measures, Maps and Taxonomies at Clare Hall, Cambridge, 2018
- The Mythical Human-Level Machine Intelligence at Philosophy and Theory of AI in Leeds, 2017
- FHI, Oxford, Aug 2016, or the very similar CSER, Cambridge, Aug 2016, about the measurement of natural and artificial intelligence
- Machine learning performance evaluation: tips and pitfalls at PAPIs Connect, 2016
- AGI 2015 Tutorial: Evaluation of Intelligent Systems
- Invited Talk at ECML Workshop on Learning over Multiple Contexts 2014
- Machine intelligence evaluation: from the Turing Test to the present Day (and beyond), for a Turing centenary celebration
Apart from the recent one on
the Evaluation of Natural and Artificial Intelligence, I've published several other
books on various topics.
I am collaborating in several national strategies for AI, in the editorial board of the Machine Learning Journal, and have served as area chair or senior PC of IJCAI, ECAI, KDD, ECML, and PC member for many others, ICML, NeurIPS, AAAI, CogSci, AGI, ICDM, UAI, ICLR, etc.
TRANSFER
We have had projects, collaborations and visits with several companies in different areas: health, retailing, software development, automotive, ...
Recently, I've been managing two "Cátedras/Aulas de Empresa":
SHORT BIO
José Hernández-Orallo is Professor at the Universitat Politècnica de València, Spain and Senior Research Fellow at the Leverhulme Centre for the Future of Intelligence, University of Cambridge, UK. He received a B.Sc. and a M.Sc. in Computer Science from UPV, partly completed at the École Nationale Supérieure de l'Électronique et de ses Applications (France), and a Ph.D. in Logic with a doctoral extraordinary prize from the University of Valencia. His academic and research activities have spanned several areas of artificial intelligence, machine learning, data science and intelligence measurement. He has published five books and more than two hundred journal articles and conference papers on these topics. His research in the area of machine intelligence evaluation has been covered by several popular outlets, such as The Economist, New Scientist or Nature. His most recent book addresses an integrated view of the evaluation of natural and artificial intelligence (Cambridge University Press, 2017, PROSE Award 2018).
IN THE MEDIA (and blogs)
Don't take this too seriously:
The
anYnt project had an extraordinary (and sometimes hilarious)
media coverage.
Blogs:
