Jan 2
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Naz
Human IQ vs Algorithmic IQ vs Deymen's IQ
Is there any scientific evidence that IQ decreases with age? My own IQ seemed higher when I was younger. Recently, I've been trying to understand Reinforcement Learning, specifically in the context of how our dog, Deymen, learns. It's not easy to model this in the context of Reinforcement Learning. I sometimes jokingly wonder if Deymen is smarter than me!
Here's a high level comparison between Human IQ and Algorithmic IQ (next time I will add 3rd Category: Deymen’s IQ):
Human IQ vs. Algorithmic IQ Improvements:
- Human IQ is traditionally measured through cognitive abilities assessments. But does Human IQ deteriorate with age, while Algorithmic IQ improves?
- Algorithmic IQ refers to AI capabilities in tasks like pattern recognition. Can it get better over time, unlike human intelligence?
Ethical Concerns of Improving Algorithmic IQ: What are the ethical implications as Algorithmic IQ continues to advance? Does its improvement pose any moral dilemmas or societal challenges?
Comparison Overview:
1. Definition and Measurement:
- Human IQ is evaluated using standardized tests.
- Algorithmic IQ measures AI system capabilities.
2. Flexibility and Adaptability:
- Human intelligence understands context and complexities.
- Algorithmic intelligence excels in specific tasks but lacks human adaptability.
3. Learning and Evolution:
- Humans learn from diverse experiences.
- Algorithms learn from data, limited to their programming.
4. Ethical and Social Considerations:
- Human decision-making is influenced by ethical and emotional factors.
- Algorithmic decisions are data-driven, potentially lacking ethical reasoning.
5. Application and Scope:
- Human intelligence is holistic, fostering creativity and innovation.
- Algorithmic intelligence is highly effective in automation and data analysis.
6. F uture Implications:
- The convergence of human and algorithmic intelligence might enhance human decision-making.
- A balanced approach could lead to significant advancements across various fields.
Understanding these differences and potential synergies is crucial as AI becomes more integrated into our society.
Free Resources:
Artificial Intelligence and Life in 2030
Artificial Intelligence and Life in 2030
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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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