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Acknowledging that there are potentially massive benefits to AI, there will be an ongoing balancing act to create, update and enforce standards and processes that maximise public welfare and safety without stifling innovation or creating unnecessary compliance burdens. Any framework developed will also have to be flexible enough to take account of both local considerations the extent of own production versus import of AI technology in each country and global considerations possible mutual recognition of safety standards and certification between countries, the need to comply with any future international treaties or conventions etc.
- Liability for Crimes Involving Artificial Intelligence Systems by Gabriel Hallevy
Screen music and the question of originality - Miguel Mera — London, Islington. Edition: Available editions United Kingdom. Robots in chains but are they really to blame when AI does something wrong? Gary Lea , Australian National University. Blame the AI robot Why not deem the robot itself liable?
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But would that approach actually make a difference here? Rules and regulations On the regulatory side, development of rigorous safety standards and establishing safety certification processes will be absolutely essential. What do we do next? Over to you. You might also like Science fiction has plenty of tales of AI turning against society including the popular Terminator movie franchise, here depicted on brick wall art.
Artificial intelligence and the law
AI researchers should work to make future battlefield robots more ethical. This is the second article in a two-part series on the social, ethical and public policy implications of the new artificial intelligence AI.
The first article briefly presented a neo-Durkheimian understanding of the social fears projected onto AI, before arguing that the common and enduring myth of an AI takeover arising from the autonomous decision-making capability of AI systems, most recently resurrected by Professor Kevin Warwick, is misplaced. That article went on to argue that, nevertheless, some genuine and practical issues in the accountability of AI systems that must be addressed.
This second article, drawing further on the neo-Durkheimian theory, sets out a more detailed understanding of what it is for a system to be autonomous enough in its decision making to blur the boundary between tool and agent. The importance of this is that this blurring of categories is often the basis, the first article argued, of social fears. Skip to Main Content. Search in: This Journal Anywhere. Advanced search.
Submit an article Journal homepage. Original Articles. Perri 6. Pages Who is responsible for any laws that are violated by the AI? Currently, one of the next big challenges that AI researchers are tackling is reinforcement learning , which is a training method that allows AI models to learn from its past experiences. Unlike other methods of generating AI models, reinforcement learning lends itself to be more like sci-fi than reality.
With reinforcement learning, we create a grading system for our model and the AI must determine the best course of action in order to get a high score. Research into complex reinforcement learning problems has shown that AI models are capable of finding varying methods to achieve positive results.
In the years to come, it might be common to see reinforcement learning AI integrated with more hardware and software solutions, from AI-controlled traffic signals capable of adjusting light timing to optimize the flow of traffic to AI-controlled drones capable of optimizing motor revolutions to stabilize videos. How will the legal system treat reinforcement learning? For example, Jones v.
It is unlikely that we will enter a dystopian future where AI is held responsible for its own actions. That certainly will pose Terminator -like dangers if AI keeps proliferating with no responsibility. The law will need to adapt to this technological change in the near future.