There's no denying it: the era of the intelligent enterprise is upon us. As technologies like AI, cognitive computing, and predictive analytics become hot topics in the corporate boardroom, sleek startups and centuries-old companies alike are laying plans for how to put these exciting innovations to work.
Gómez, Emilia, Castillo, Carlos, Charisi, Vicky, Dahl, Verónica, Deco, Gustavo, Delipetrev, Blagoj, Dewandre, Nicole, González-Ballester, Miguel Ángel, Gouyon, Fabien, Hernández-Orallo, José, Herrera, Perfecto, Jonsson, Anders, Koene, Ansgar, Larson, Martha, de Mántaras, Ramón López, Martens, Bertin, Miron, Marius, Moreno-Bote, Rubén, Oliver, Nuria, Gallardo, Antonio Puertas, Schweitzer, Heike, Sebastian, Nuria, Serra, Xavier, Serrà, Joan, Tolan, Songül, Vold, Karina
This document contains the outcome of the first Human behaviour and machine intelligence (HUMAINT) workshop that took place 5-6 March 2018 in Barcelona, Spain. The workshop was organized in the context of a new research programme at the Centre for Advanced Studies, Joint Research Centre of the European Commission, which focuses on studying the potential impact of artificial intelligence on human behaviour. The workshop gathered an interdisciplinary group of experts to establish the state of the art research in the field and a list of future research challenges to be addressed on the topic of human and machine intelligence, algorithm's potential impact on human cognitive capabilities and decision making, and evaluation and regulation needs. The document is made of short position statements and identification of challenges provided by each expert, and incorporates the result of the discussions carried out during the workshop. In the conclusion section, we provide a list of emerging research topics and strategies to be addressed in the near future.
One of the ambitions of artificial intelligence is to root artificial intelligence deeply in basic science while developing brain-inspired artificial intelligence platforms that will promote new scientific discoveries. The challenges are essential to push artificial intelligence theory and applied technologies research forward. This paper presents the grand challenges of artificial intelligence research for the next 20 years which include:~(i) to explore the working mechanism of the human brain on the basis of understanding brain science, neuroscience, cognitive science, psychology and data science; (ii) how is the electrical signal transmitted by the human brain? What is the coordination mechanism between brain neural electrical signals and human activities? (iii)~to root brain-computer interface~(BCI) and brain-muscle interface~(BMI) technologies deeply in science on human behaviour; (iv)~making research on knowledge-driven visual commonsense reasoning~(VCR), develop a new inference engine for cognitive network recognition~(CNR); (v)~to develop high-precision, multi-modal intelligent perceptrons; (vi)~investigating intelligent reasoning and fast decision-making systems based on knowledge graph~(KG). We believe that the frontier theory innovation of AI, knowledge-driven modeling methodologies for commonsense reasoning, revolutionary innovation and breakthroughs of the novel algorithms and new technologies in AI, and developing responsible AI should be the main research strategies of AI scientists in the future.
"Imagine a scenario in which self-driving cars fail to recognize people of color as people--and are thus more likely to hit them--because the computers were trained on data sets of photos in which such people were absent or underrepresented," Joy Buolamwini, a computer scientist and researcher at MIT, told Fortune in a recent interview. Buolamwini's research revealed that facial recognition software from tech giants Microsoft, IBM and Amazon, among others could identify lighter-skinned men but not darker-skinned women. It happens because of something that is mounting alarm: algorithmic bias. Algorithms are the foundation of machine learning. They are what drives intelligent machines to make decisions.
"With great power, comes great responsibility" I remember hearing this dialogue in the Spider-Man movie where Uncle Ben schools a young Peter Parker on the travails of wielding power in life. In the context of Artificial Intelligence, this phrase could not be more relevant. Artificial Intelligence is widely being heralded as General Purpose Technology by many economists – one with a range of characteristics that make it poised to generate long-term productivity and economic growth. The onus of bailing out economies out of turmoil and provide a foundation for a new world order falls on AI, in these COVID times especially. This makes the debate around ethical AI is extremely pertinent today. How can AI be ethical?