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Mapping Intelligence: Requirements and Possibilities

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Philosophy and Theory of Artificial Intelligence 2017 (PT-AI 2017)

Part of the book series: Studies in Applied Philosophy, Epistemology and Rational Ethics ((SAPERE,volume 44))

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Abstract

New types of artificial intelligence (AI), from cognitive assistants to social robots, are challenging meaningful comparison with other kinds of intelligence. How can such intelligent systems be catalogued, evaluated, and contrasted, with representations and projections that offer meaningful insights? To catalyse the research in AI and the future of cognition, we present the motivation, requirements and possibilities for an atlas of intelligence: an integrated framework and collaborative open repository for collecting and exhibiting information of all kinds of intelligence, including humans, non-human animals, AI systems, hybrids and collectives thereof. After presenting this initiative, we review related efforts and present the requirements of such a framework. We survey existing visualisations and representations, and discuss which criteria of inclusion should be used to configure an atlas of intelligence.

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Notes

  1. 1.

    A detailed analysis of the questionnaire can be found in (Bhatnagar et al. 2017).

  2. 2.

    Some of these initiatives are in genomics and brain imaging (Midford 2004; Boero and Bernardi 2014).

  3. 3.

    http://www.cognitiveatlas.org.

  4. 4.

    https://poldracklab.stanford.edu/.

  5. 5.

    http://observatory.brain-map.org/visualcoding/.

  6. 6.

    http://buros.org/mental-measurements-yearbook.

  7. 7.

    http://ipip.ori.org.

  8. 8.

    http://icar-project.com.

  9. 9.

    http://www.kaggle.com.

  10. 10.

    http://www.openml.org.

  11. 11.

    http://www.arcadelearningenvironment.org/.

  12. 12.

    https://gym.openai.com/.

  13. 13.

    https://www.microsoft.com/en-us/research/project/project-malmo/.

  14. 14.

    https://research.fb.com/projects/commai/.

  15. 15.

    https://deepmind.com/blog/open-sourcing-deepmind-lab/.

  16. 16.

    http://www.eff.org/ai/metrics.

  17. 17.

    http://aiindex.org.

  18. 18.

    http://www.roadmapinstitute.org.

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Acknowledgements

The initiative was supported by the Leverhulme Trust via the Leverhulme Centre for the Future of Intelligence. J. H-Orallo and F. M-Plumed were supported by EU (FEDER) and the Spanish MINECO under grant TIN 2015-69175-C4-1-R and by GVA under grant PROMETEOII/ 2015/013 and by the Air Force Office of Scientific Research under award number FA9550-17-1-0287. J. H-Orallo also received a Salvador de Madariaga grant (PRX17/00467) from the Spanish MECD for a research stay at the CFI, Cambridge, and a BEST grant (BEST/2017/045) from the GVA for another research stay also at the CFI. F. M-Plumed was also supported by INCIBE (Ayudas para la excelencia de los equipos de investigación avanzada en ciberseguridad). A. Weller acknowledges support from the David MacKay Newton research fellowship at Darwin College, the Alan Turing Institute under EPSRC grant EP/N510129/1 & TU/B/000074, and the Leverhulme Trust via the CFI.

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Authors and Affiliations

  1. Leverhulme Centre for the Future of Intelligence, Cambridge, UK

    Sankalp Bhatnagar, Anna Alexandrova, Stephen Cave, Lucy Cheke, Matthew Crosby, Marta Halina, Seán Ó hÉigeartaigh, Huw Price, Henry Shevlin, Adrian Weller, Alan Winfield & José Hernández-Orallo

  2. The New School, New York, USA

    Sankalp Bhatnagar

  3. Centre for the study of Existential Risk, University of Cambridge, Cambridge, UK

    Shahar Avin, Seán Ó hÉigeartaigh & Huw Price

  4. Department of History and Philosophy of Science, University of Cambridge, Cambridge, UK

    Anna Alexandrova & Marta Halina

  5. Psychometrics Centre, University of Cambridge, Cambridge, UK

    Bao Sheng Loe

  6. Universitat Politècnica de València, València, Spain

    Fernando Martínez-Plumed & José Hernández-Orallo

  7. Imperial College, London, UK

    Matthew Crosby

  8. AI Roadmap Institute, Prague, Czech Republic

    Jan Feyereisl

  9. GoodAI, Prague, Czech Republic

    Jan Feyereisl

  10. Bristol Robotics Laboratory, UWE Bristol, Bristol, UK

    Alan Winfield

  11. Department of Psychology, University of Cambridge, Cambridge, UK

    Lucy Cheke

  12. Alan Turing Institute, London, UK

    Adrian Weller

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    Vincent C. Müller

A Appendix: Why is an atlas needed? Similar initiatives

A Appendix: Why is an atlas needed? Similar initiatives

While identifying the need for an atlas, we look at how it fits in cognitive science as a whole and also whether there are initiatives in other fields that could be inspirational.

Regarding cognitive science, it is true that its goal is to cover all possible cognitive systems, understand their behaviour and mechanisms, and establish meaningful comparisons. However, the field has not yet been able to portray a systematic representation covering both natural and artificial systems. But if we do not find this systematic representation in cognitive science, do we find it in related subdisciplines? The answer is that some similar initiatives in other disciplines do existFootnote 2:

  • Life forms: Examples are Wikispecies (Leslie 2005), the All Species Foundation (Gewin 2002), the Catalogue of Life and the Encyclopedia of Life (Roskov et al. 2018; Hayles 1996; Parr et al. 2014; Stuart et al. 2010).

  • Neuroscience: the Cognitive AtlasFootnote 3 and related repositories for neuroscienceFootnote 4 include an ontology of human cognitive functions and related tasks, and the pathologies affected. The Allen brain observatoryFootnote 5 (Allen Institute for Brain Science 2016) is a more visually-oriented platform that maps perception and cognition to parts of the human brain (National Research Council 2011).

  • Psychometrics: There are several initiatives bringing together test batteries and repositories: the mental Measurement yearbookFootnote 6, and with a more open character, the International Personality Item PoolFootnote 7 and the International Cognitive Ability ResourceFootnote 8.

  • Machine learning and data science research: KaggleFootnote 9, OpenMLFootnote 10 (Vanschoren et al. 2013) and many other platforms (e.g., gitxiv.com) provide benchmarks for ML. OpenML also includes experimental results that can be compared, aggregated and represented with powerful analytical packages.

  • Artificial intelligence: there are many collections of benchmarks and associated results, such as ALEFootnote 11, OpenAI universe/gymFootnote 12, Microsoft MalmoFootnote 13, Facebook’s CommAI-envFootnote 14, DeepMind LabFootnote 15 (see Hernández-Orallo et al. 2017 for a summary) and meta-views, such as a recent EFF analysisFootnote 16 and the AI index reportFootnote 17. This is a sign that AI is looking in this direction (Castelvecchi 2016; Hernández-Orallo 2017). The tasks are rarely arranged into abilities and the data usually compares specialised AI systems against average humans.

A partially overlapping initiative is the AI Roadmap InstituteFootnote 18, which encourages, compares and studies various AI and general AI roadmaps. It focuses on the future and on AI primarily, with representations that are usually flowcharts and pathway comparisons. Besides identifying where the field of AI stands as a whole, it also aims to identify dead-ends and open research problems on the path to the development of general AI systems.

The data and conceptual framing of the above projects can be used to inform an atlas of intelligence. Still, no repositories or taxonomies exist focusing mostly on behaviour, encompassing natural and artificial systems, as we are undertaking. Of course, the fact that something does not exist yet is not a sufficient reason that it should. The need for an atlas has to be supported by a series of motivations and applications, which we do in Sect. 2.

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Bhatnagar, S. et al. (2018). Mapping Intelligence: Requirements and Possibilities. In: Müller, V. (eds) Philosophy and Theory of Artificial Intelligence 2017. PT-AI 2017. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 44. Springer, Cham. https://doi.org/10.1007/978-3-319-96448-5_13

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