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An essential collection on AI safety and - Häggström hävdar

For example, on the theoretical end, our interests include models of causal influence, and the limitations of value learning. On the experimental side, we have been interested in training deep learning models to decompose complex tasks, and to be more robust to large errors. My read of the AI safety space is that there are currently two major approaches to AGI alignment being researched: agent foundations and agent training. We can contrast them in part by saying the ultimate goal of the agent foundations program is… uncertainty calibration ai-safety robustness adversarial-examples pretrained data-corruption out-of-distribution-detection Updated May 15, 2019 Python 2019-02-19 · AI Safety Needs Social Scientists. Properly aligning advanced AI systems with human values will require resolving many uncertainties related to the psychology of human rationality, emotion, and biases. These can only be resolved empirically through experimentation — if we want to train AI to do what humans want, we need to study humans.

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We read “Superintelligence: Paths Dangers, Strategies” by Nick Bostrom, and “How viable is arms control… Packing safety intelligence into robots’ AI brains We’re finding that smart robots don’t necessarily have the common sense needed to keep human beings out of harm’s way. Packing safety intelligence into robots’ AI brains We’re finding that smart robots don’t necessarily have the common sense needed to keep human beings out of harm’s way. Artificial intelligence (AI), machine learning (ML), and Internet of things (IoT) enablement are transforming business and offer significant opportunity to improve the health and safety of your employees. On-the-job tragedies have an irreversible impact on families and friends and put employee morale and company reputation at risk. There are indeed plenty of AI applications that make our everyday lives more convenient and efficient.

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Artificial Intelligence (AI) Safety can be broadly defined as the endeavour to ensure that AI is deployed in ways that do not harm human ity.This definition is easy to agree with, but what does it actually mean? AI Safety is collective termed ethics that we should follow so as to avoid problem of accidents in machine learning systems, unintended and harmful behavior that may emerge from poor design of real-world AI systems. Center for AI Safety The mission of the Stanford Center for AI Safety is to develop rigorous techniques for building safe and trustworthy AI systems and establishing confidence in their behavior and robustness, thereby facilitating their successful adoption in society. Read more in the white paper AI Safety Research “What we really need to do is make sure that life continues into the future. By focusing our AI Safety Holdings Consortium on key Healthcare Companies for M&A, we will bring together mid-size AI market leaders to address the issues in the Healthcare Industry today. The AI Safety Research Program was a four-month-long project bringing together talented students and junior researchers with a deep interest in long-term AI safety research, aiming to together create a creative and inspiring research environment, help prospective alignment researchers work on AI safety research problems, gain a better understanding of the AI alignment field, improve their research skills, and bring them closer to the existing research community.

We think solving the AI control problem is one of the world’s most important and neglected research questions. The development of powerful AI also brings major political and social challenges. AI policy is fast becoming an important area, but policy-makers are mostly focused on short-term issues like how to regulate self-driving cars, rather than the key long-term issues such as the Organizers of the AI Safety Camp are volunteers and mainly past participants. Contact current organizers at contact@aisafety.camp or schedule a one-on-one phone call. The call doesn’t have to be as long as the scheduling site indicates. If you have a five-minute question, we’re happy to get on a call for only five minutes. Current edition #5.
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AI policy is fast becoming an important area, but policy-makers are mostly focused on short-term issues like how to regulate self-driving cars, rather than the key long-term issues such as the Organizers of the AI Safety Camp are volunteers and mainly past participants. Contact current organizers at contact@aisafety.camp or schedule a one-on-one phone call. The call doesn’t have to be as long as the scheduling site indicates. If you have a five-minute question, we’re happy to get on a call for only five minutes. Current edition #5. analyzing safety of the AI-based systems at all levels.

In fact, in 1930 the economist John Maynard Keynes predicted that automation and technology advancements would eventually leave us with a 15-hour work week. Se hela listan på 80000hours.org This is a science and engineering based forum created to discuss the various aspects of AI and AGI safety. Topics may include research, design, AI Safety Camp connects you with interesting collaborators worldwide to discuss and decide on a concrete research proposal, gear up online as a team, and try your hand at AI safety research during intensive coworking sprints. Our second virtual edition takes place from mid-January to the end of May 2021. Applications have now closed. Arguing for AI safety is “arguing against being able to better diagnose people when they’re sick.” All this talk about regulations and ethics and safety is just slowing down cancer diagnoses AI safety outreach: Co-organized FLI’s Beneficial AGI conference in Puerto Rico, a more long-term focused sequel to the original Puerto Rico conference and the Asilomar conference. This year I was the program chair for the technical safety track of the conference.
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AI for Vehicle Safety According to a Stanford study from 2013, roughly 90% of vehicle crashes are due to human error, at least in part. The idea for a solution, then, is to remove the possibility for human error by automating vehicles to operate on their own. In 2018, Telefónica released their Principles of AI, committing to designing, developing, and using AI with integrity, across their own operations and that of their suppliers and partners. Their principles underscore fairness, transparency and explainability, human-centeredness, and privacy and security.

We do technical research aimed at ensuring that smarter-than-human AI systems have a positive impact on the world. 2019-03-20 · Artificial Intelligence (AI) Safety can be broadly defined as the endeavour to ensure that AI is deployed in ways that do not harm human ity. This definition is easy to agree with, but what does it actually mean? Well, to complement the many ways that AI can better human lives, there are unfortunately many ways that AI can cause harm. In spring of 2018, FLI launched our second AI Safety Research program, this time focusing on Artificial General Intelligence (AGI) and how to keep it safe and beneficial. By the summer, 10 researchers were awarded over $2 million to tackle the technical and strategic questions related to preparing for AGI, funded by generous donations from Elon Musk and the Berkeley Existential Risk Institute.
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Eirin Evjen and Markus Anderljung, AI Safety - Human - Podtail

We do technical research aimed at ensuring that smarter-than-human AI systems have a positive impact on the world. This page outlines in broad strokes why we view this as a critically important goal to work toward today. Artificial Intelligence (AI) Safety can be broadly defined as the endeavour to ensure that AI is deployed in ways that do not harm human ity.This definition is easy to agree with, but what does it actually mean?

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“Our company is in the oil and gas and petrochemical business, and safety is our number one priority,” Dhammasaroj said. Regulating AI-based systems: safety standards and certification. Human-in-the-loop and the scalable oversight problem. Evaluation platforms for AI safety. AI safety education and awareness.

Another way of looking at the issue is to reframe problems with AI as challenges to overcome and opportunities to improve. For example, if an AI car has an accident, there is some debate about whose fault that is. AI has the potential to make a substantial impact for individuals, communities, and society. To make sure the impact of your AI project is positive and does not unintentionally harm those affected Safety in AI is important, but more important is to work it out before working out the AI itself. Rob Miles on AI safety.Brain Scanner: https://youtu.be/TQ0s Applications of AI in Workplace Safety Thanks to computing power, a full office working day in 1970 can now be completed in 1.5 hours. Amazing, right?