#38 Learning tomorrow : Artificial Intelligence & neuroscience working hand in hand with Alexia Audevart

Let's talk Transformation...

"We are already living in the century of the brain" : What is the future of humanity and how do we learn in an increasingly digital world ? How do AI and neuroscience compliment each other ?

Alexia and I have a conversation around bringing technology and neuro-cognition together : demystifying AI, neuroscience and what it brings to the learning landscape. AI is changing our world; the technological and neuro-revolution is transforming how we live and work, and our relationships with others. AI also plays a decisive role in the competitiveness of companies of all sizes and is revolutionising many sectors (e.g. marketing, CX, etc). All businesses are impacted, and companies must accept these new tools both to optimise tasks previously performed by humans and to constantly navigate change in an emerging environment.

Alexia shares insights and experience from her research and work with companies both big and small.

The main insights you will get from this episode are :

• Creating value through technology means bridging the gap between human value and technological value and promoting diversity in technology. Data and technology are ever more present and connect us in ways we never thought possible.
• Neuroscience brings AI and human intelligence together. AI dates back to 1956 when scientists dreamt of recreating human cognitive functions in machines and unravelling the mysteries of intelligence (the Latin ‘intelligere’ means ‘the ability to make connections’).
• Machine learning is based on statistical AI and data. Traditional programming uses computer data and is always accurate. ML on the other hand is not always accurate: it uses statistical information to create links, ‘learn’ and then make predictions (modelling).
• Narrow AI currently only covers simple, repetitive, specialised tasks. In some cases, AI outperforms humans, but machines cannot generalise and cannot yet go from narrow AI to general AI. We are learning more about neuro-cognition: AI learns quickly, and so must we.
• Deep learning has led to major advances: artificial neural networks make simple calculations, with each layer deepening the level of understanding. This process is bio-inspired, analysing large amounts of data using computer science, mathematics and AI to gain a better understanding of how the human brain works.
• How is AI regulated from an ethical point of view? Will there be universal rules for AI? Do we need new legislation? It is difficult to define an international ethical framework because different factors mean different results in different countries.
• The ethics question has long been debated but we can start with robotics (cf. Asimov’s laws): those developing the systems must seek to answer questions during the design phase (ethics by design).
• What is the future of humanity? Will AI destroy the human race? What changes are expected? We are already living in the century of the brain, which has given rise to many ‘neuro-disciplines’ such as neuro-education, neuro-economics, neuro-law.
• AI is changing our world; the technological and neuro-revolution is transforming how we live and work, and our relationships with others; it is also multidisciplinary, i.e. human, cultural and societal. AI is at the heart of other sciences, with a theoretical basis in statistics and mathematics but in combination with the human science of biology.
• It plays a decisive role in the competitiveness of companies of all sizes and is revolutionising many sectors (e.g. marketing, CX, etc). All businesses are impacted, and companies must accept these new tools both to optimize tasks previously performed by humans and to constantly navigate change in an emerging environment.
• We must all understand the important concepts of AI: what it is, what machines can do, what the AI use cases are, what its impact will be on business, processes and us. We must educate ourselves, not be afraid and be open-minded to the amazing possibilities of AI.