Feb 4
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Naz
What if AI Learns in Its Own Way?
Have you ever wondered why, in our quest to advance AI, we often aim to create 'digital humans' that mimic our behaviors and thought processes? While it's fascinating to see machines reflecting human intelligence, this approach leads to a critical question: Are we missing an opportunity to innovate beyond our limitations?
AI, fundamentally, has the potential to not only replicate but also transcend human capabilities. By focusing on creating AI that mirrors us, are we unconsciously imposing our own limitations on these systems, including the flaws and biases accumulated throughout history?
Imagine the possibilities if we ventured into uncharted territories of intelligence, unique to AI itself. Could we unlock new forms of problem-solving, creativity, and understanding that are currently beyond human grasp?
Here are some thought-provoking directions for AI learning:
✔ Non-Linear Learning Models: Moving away from human-like linear progression to multi-dimensional learning, enabling AI to make novel connections.
✔ Quantum Computing Integration: Harnessing quantum mechanics principles for enhanced problem-solving capabilities.
✔ Bio-Inspired Algorithms: Learning from a broad range of biological processes beyond human cognition.
✔ Embracing AI's Innate Abilities: Leveraging AI’s capability to process vast data sets for pattern recognition.
✔ Collaborative Learning with Nature: Adapting in real-time to environmental changes through embodied cognition.
✔ Decentralized Intelligence Models: Developing a collective learning approach akin to a hive mind.
✔ Cross-Disciplinary Integration: Merging arts, philosophy, and sociology with technology for holistic learning.
✔ Emotional and Intuitive Learning: Integrating emotional intelligence and intuition-based algorithms.
✔ Ethical Decision-Making: Creating AI that adapts ethical guidelines based on global values.
What if, instead of teaching AI to learn like us, we let it learn in its own, perhaps more efficient or novel ways? This could lead to breakthroughs we haven't even considered yet.
Let's think about it: Should the future of AI involve diverging from the path of human imitation to explore its unique potential? What kind of unprecedented innovations could this lead to?
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Ali Hessami is currently the Director of R&D and Innovation at Vega Systems, London, UK. He has an extensive track record in systems assurance and safety, security, sustainability, knowledge assessment/management methodologies. He has a background in the design and development of advanced control systems for business and safety-critical industrial applications.
Hessami represents the UK on the European Committee for Electrotechnical Standardization (CENELEC) & International Electrotechnical Commission (IEC) – safety systems, hardware & software standards committees. He was appointed by CENELEC as convener of several Working Groups for review of EN50128 Safety-Critical Software Standard and update and restructuring of the software, hardware, and system safety standards in CENELEC.
Ali is also a member of Cyber Security Standardisation SGA16, SG24, and WG26 Groups and started and chairs the IEEE Special Interest Group in Humanitarian Technologies and the Systems Council Chapters in the UK and Ireland Section. In 2017 Ali joined the IEEE Standards Association (SA), initially as a committee member for the new landmark IEEE 7000 standard focused on “Addressing Ethical Concerns in System Design.” He was subsequently appointed as the Technical Editor and later the Chair of P7000 working group. In November 2018, he was appointed as the VC and Process Architect of the IEEE’s global Ethics Certification Programme for Autonomous & Intelligent Systems (ECPAIS).
Trish advises and trains organisations internationally on Responsible AI (AI/data ethics, policy, governance), and Corporate Digital Responsibility.
Patricia has 20 years’ experience as a lawyer in data, technology and regulatory/government affairs and is a registered Solicitor in England and Wales, and the Republic of Ireland. She has authored and edited several works on law and regulation, policy, ethics, and AI.
She is an expert advisor on the Ethics Committee to the UK’s Digital Catapult Machine Intelligence Garage working with AI startups, is a Maestro (a title only given to 3 people in the world) and expert advisor “Maestro” on the IEEE’s CertifAIEd (previously known as ECPAIS) ethical certification panel, sits on IEEE’s P7003 (algorithmic bias)/P2247.4 (adaptive instructional systems)/P7010.1 (AI and ESG/UN SDGS) standards programmes, is a ForHumanity Fellow working on Independent Audit of AI Systems, is Chair of the Society for Computers and Law, and is a non-exec director on the Board of iTechlaw and on the Board of Women Leading in AI. Until 2021, Patricia was on the RSA’s online harms advisory panel, whose work contributed to the UK’s Online Safety Bill.
Trish is also a linguist and speaks fluently English, French, and German.
In 2021, Patricia was listed on the 100 Brilliant Women in AI Ethics™ and named on Computer Weekly’s longlist as one of the Most Influential Women in UK Technology in 2021.
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