Matthew Griffin, award winning Futurist working between the dates of 2020 and 2070, is described as “The Adviser behind the Advisers” and a “Young Kurzweil.” Regularly featured in the global press, including BBC, CNBC, Discovery and RT, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew sits on several boards and his recent work includes mentoring Lunar XPrize teams, building the first generation of biological computers and re-envisioning global education with the G20, and helping the world’s largest manufacturers ideate the next 20 years of intelligent devices and machines. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Bain & Co, BCG, BOA, Blackrock, Bentley, Credit Suisse, Dell EMC, Dentons, Deloitte, Du Pont, E&Y, HPE, Huawei, JPMorgan Chase, KPMG, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, UBS, and many more.
WHY THIS MATTERS IN BRIEF
- Whether they’re hardware based, or software based, machines are getting increasingly capable, creative, intelligent and resilient – and that has experts worried, so now they’ve created a new set of laws to try to guide the technology’s development and trajectory
Ever since people first discussing the concept of robots and “mechanical men” humans have been fascinated, not just by the frailty of our own existence but also about the possibility of a robo-rebellion, led by machines that are more intelligent, and more capable than us, and that could potentially, by all definitions, be immortal.
In 1942 Isaac Asimov, one of the greatest science fiction writers of all time, devised one of the world’s most captivating laws for his book the “Handbook of Robotics, 56th Edition, 2058 AD.” Known as the Three Laws of Robotics many people have considered them to be the main go to laws that should govern today’s mechanical men, or “Electronic Persons” – the legal status that the EU will give them later this year. But life, law and technology is more complicated than that.
Part of the Three Laws appeal is that they are so simple, and people like simple.
Asimov’s Three Laws
1. A robot may not injure a human being or, through inaction, allow a human being to come to harm
2. A robot must obey the orders given it by human beings except where such orders would conflict with the First Law
3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws
For anyone who’s ever watched a film like the Terminator series most of us know that there are some dangers associated with the path that society is racing down – whether that’s because we’re busy creating robots in our own image, or creating new intelligent machines that one day soon will exceed human intelligence. Or, maybe it’s simply because we’re creating fully autonomous weapons systems that can carry and launch nuclear weapons… something that the UN will take a vote on banning later this year.
But let’s not dwell on that, I’m sure it’ll all be fine in the end. Whatever that end is.
Fortunately for society though not everyone is so blasé and over the course of the past year a total of 892 artificial intelligence (AI) and robotics researchers, and 1445 other experts, many of whom also signed an open letter on the dangers of AI, have all gotten together to create and endorse a list of 23 guiding principles that should steer AI development in a productive, ethical, and safe direction.
The Asilomar AI Principles as they are now known were developed after the brought dozens of experts together for their Beneficial AI 2017 conference. The experts, whose ranks consisted of roboticists, physicists, economists, philosophers, and more had fierce debates about AI safety, economic impact on human workers, programming ethics and much more, and in order for a new principle to make the final list, 90 percent of the experts had to agree on its inclusion.
“What remained was a list of 23 principles ranging from research strategies to data rights to future issues including potential super-intelligence, which was signed by those wishing to associate their name with the list,” the Future of Life’s director said in a statement, “this collection of principles is by no means comprehensive and it’s certainly open to differing interpretations, but it also highlights how the current ‘default’ behaviour around many relevant issues could violate principles that most participants agreed are important to uphold.”
It could be argued that all of the principles, such as transparency and open research among competitive companies, are all a step in the right direction and will help drive the ethical development of new AI’s. However, while the principles might be taken on board and abided by by human scientists and researchers, whether or not they’ll be taken to heart by the AI’s who are now making more AI’s, or who soon might be running the companies in question, could be open to debate. Here’s a list of them:
The Asimolar AI Principles
1. Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence
2. Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies
3. Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers
4. Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI
5. Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards
6. Safety: A.I. systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible
7. Failure Transparency: If an AI system causes harm, it should be possible to ascertain why
8. Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority
9. Responsibility: Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications
10. Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation
11. Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity
12. Personal Privacy: People should have the right to access, manage and control the data they generate, given AI systems power to analyze and utilize that data
13. Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty
14. Shared Benefit: AI technologies should benefit and empower as many people as possible
15. Shared Prosperity: The economic prosperity created by AII should be shared broadly, to benefit all of humanity
16. Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives
17. Non-subversion: The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends
18. AI Arms Race: An arms race in lethal autonomous weapons should be avoided
19. Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities
20. Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources
21. Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact
22. Recursive Self-Improvement: AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures
23. Common Good: Super-intelligence should only be developed in the service of widely shared ethical ideals, and for the benefit of all humanity rather than one state or organization