Colin Lewis

Colin Lewis
The London School of Economics and Political Science | LSE · Centre for Economic Performance (CEP)

Ph.D.

About

8
Publications
4,224
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62
Citations
Citations since 2017
8 Research Items
62 Citations
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Introduction
Research scientist in intelligence and AI. Lecturer and international consultant specialized in the social and economic impact of technological change. Core research is 'Intelligence." I generally focus on topics within Artificial Intelligence, Behavioural Economics & Data Science, with a specific focus on understanding intelligence and creating AI that benefits humanity. Further research focuses on technology automation, robotics and artificial intelligence and their impact on society.

Publications

Publications (8)
Conference Paper
Full-text available
We posit that the lack of consensus definitions of (machine or artificial) intelligence might be affected by the lack of knowledge of conceptual analysis and other well-investigated theories. Acute contextualization of the concepts that are defined may also be an issue. Accordingly, in this two-part paper, we review some basic concepts from across...
Conference Paper
Full-text available
We posit that the lack of consensus definitions of (machine or artificial) intelligence might be affected by the lack of knowledge of conceptual analysis and other well-investigated theories. Acute contextualization of the concepts that are defined may also be an issue. Accordingly, in this two-part paper, we review some basic concepts from across...
Conference Paper
Full-text available
There are several reasons for the lack of a consensus definition of (machine) intelligence. The constantly evolving nature and the interdisciplinarity of the Artificial Intelligence (AI) field, together with a historical polarization around what intelligence means, are among the most widely discussed rationalizations, both within the community and...
Chapter
Full-text available
Intelligence remains ill-defined. Theories of intelligence and the goal of Artificial Intelligence (A.I.) have been the source of much confusion both within the field and among the general public. Studies that contribute to a well-defined goal of the discipline and spread a stronger, more coherent message, to the mainstream media, policy-makers, in...
Conference Paper
Full-text available
Human intelligence is a quality recognized as showing differences between individuals. For more than 150 years researchers have been studying and continually improving psychometric tests for human intelligence, with a colossal amount of data collected; however, despite many attempts, there remains no clearly agreed upon definition of human intellig...

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Projects

Projects (5)
Project
A recent survey of Artificial Intelligence (AI) educators by Michael Wollowski, Peter Norvig and others (Wollowski et al., 2016) showed a stark difference of opinion about the definition of Artificial Intelligence. We invite you to participate in our survey (https://goo.gl/hMjaE1) to gather opinions on definitions of intelligence and Machine Intelligence from leading researchers in AI, Neuroscience, Psychology, and other disciplines, ultimately to help create a unified message on the goal and definition of AI. Understanding intelligence and how it may be recreated (and measured) is one of the major scientific challenges of our time. Our research shows that theories of intelligence and the goal of AI have been the source of much confusion both within the field and among the general public. Toward an agreed upon definition and ultimate research goal As researchers we are aware that a robust definition is usually the result, rather than the starting point, of scientific research, nevertheless an agreed upon working definition of Machine Intelligence and an ultimate research goal could help the next stage of AI development. In the opening sentence of Nils J. Nilsson's book (2010), The Quest for Artificial Intelligence. A History of Ideas and Achievements, he states: “Artificial intelligence may lack an agreed-upon definition.” We hope the results of our study, which will also include a rigorous review of the literature, will help inform academics, researchers, and practitioners with respect to an agreed upon definition of AI from the widest number of practitioners and researchers, and in so doing help towards the creation of building something like an artificial scientist to benefit humanity. Furthermore, AI has a perception problem in the mainstream media even though many researchers indicate that supporting humanity must be the goal of AI. By clarifying the known definitions of intelligence and research goals of Machine Intelligence this should help us and other AI practitioners spread a stronger, more coherent message, to the mainstream media, policymakers, and the general public to help dispel myths about AI. The survey (https://goo.gl/hMjaE1) is completed anonymously but if you would like to be notified when the paper is available or have your definition of intelligence be considered for inclusion (with your name alongside) in our coming research paper, then there is also the opportunity to add your name and email address. Please send an invitation to any people that you feel may be interested and could contribute toward this important principle. The survey is available here: https://goo.gl/hMjaE1. Dr. Colin W. P. Lewis Ph.D. in Behavioral Economics and Data Science Robotenomics.com, AGI Sentinel Initiative (AGISI.org) Prof. Dr. Dagmar Monett Ph.D. in Computer Science Berlin School of Economics and Law, AGI Sentinel Initiative (AGISI.org)
Project
A long-term goal of Artificial Intelligence researchers is to understand intelligence.[1, 2] To date, the vast majority of these researchers follow a long tread path of neuron research. For over two centuries, the study of brain function has been dedicated to extracting the importance of neurons – cells that have long been known to convey and receive information that links our sensory experience to the world around us. The study of neuronal function has been instrumental in guiding our understanding of neural physiology and clinical neurology. However, the neuronal paradigm of studying brain function has left us with major limitations in our understanding of how the brain translates basic stimuli to higher order cognitive functions in humans. In fact, analyses show that neuronal properties are remarkably similar across species. The human brain is a tangled mass of synapses, neurons, dendrites, axons, and glial cells. The research project Understanding Intelligence will specifically seek to help discover the role astrocytes (glia cells) play in memory, learning, and cognitive development (such as creativity, thinking, reasoning, logic). "Although the intellectual capacity of humans exceeds that of other species... it seems unlikely that the increased functional competence of the human brain can be attributed to any discrete aspect of neuronal number, form or function".[3] It is more likely "the astrocytic domain might extend the processing power of human brain beyond that of other species".[3] Key question: Are there prominent features of astrocytes in the human brain that contribute significantly to intelligence and cognition? Researchers now know that astrocytes play many active roles and are critical for the development, information processing, and function of the Central Nervous System and brain plasticity. Further, "[a]strocytes can control synaptic networks and in such a capacity they may represent an integral and overlooked component of the computational power of the brain".[4] Indeed it is thought that virtually every aspect of brain development and function involves a neuron-glial partnership and that the "versatility of astrocytes is key to the development of human intelligence".[5] Understanding the importance of astrocytes and how they might contribute to the increased processing power of the human brain "could be the crack in the door that lets us understand the brain's code".[6] Furthermore, understanding the brain's code will lead to being able to build human-level intelligent devices. Finally, we believe a combined understanding of the brain together with the development of intelligent devices will contribute to significantly improving the quality of life for all human beings. References: 1. Stuart Russell (1997). Rationality and Intelligence. Artificial Intelligence, 94(1–2):57-57, Elsevier. 2. Stuart Russell (2014). Rationality and Intelligence: A Brief Update. In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library). Berlin: Springer. 3. Nancy Ann Oberheim, Xiaohai Wang, Steven Goldman, and Maiken Nedergaard (2006). Astrocytic complexity distinguishes the human brain. TRENDS in Neuroscience, 29(10):547-553, Elsevier. 4. Alexei Verkhratsky, Vladimir Parpurac, and José J. Rodríguez (2011). Where the thoughts dwell: The physiology of neuronal–glial "diffuse neural net". Brain Research Reviews, 66(1-2):133-151, Elsevier B.V. 5. José J. Rodríguez, Arthur M. Butt, Emanuela Gardenal, Vladimir Parpura, and Alexei Verkhratsky (2016). Complex and Differential Glial Responses in Alzheimer's Disease and Ageing. Current Alzheimer Research, 13(4):343-358, Bentham Science Publishers. 6. Dr. Terrence Sejnowski (2014). Astrocytes help the brain to remember. Salk Institute.
Project
The promise of general intelligence in machines has yet to be realized. We are committed to making this happen in our lifetime. Our approach is based on a constructivist foundation for knowledge acquisition and hypothesize that general intelligence may be realized via pee-wee size atomic knowledge models in a system supporting value-driven scheduling, integrated domain-independent prediction-planning processes, and ampliative reasoning. Our AERA system prototype of these ideas have shown highly promising results, supporting incremental continuous ("life-long") learning of highly complex tasks.