Now more than ever, AI needs a governance framework 

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Is the author Stanford Institute for Human-Center AI (HAI) and CEO and World Labs co-founder Founder Founder Founder Founder

Artificial intelligence is moving at the speed of a separation. The days of the calculation models were used to accept what the days were used to be done in minutes and training costs have increased dramatically, they will soon come down to learn to do more with less. I said it before, and I will repeat it – the future of AI is now.

This is not surprising to anyone in the field. Computer scientists have worked hard; Companies have been innovating for years. Amazingly-and eyebrows-which is a lack of an excessive structure for the AI ​​administration. Yes, AI is making fast progress – and with this it is necessary to confirm that it benefits all humanity.

As a technician and educator, I feel strongly that everyone in the Global AI ecosystem is responsible for taking the technology forward and ensuring a human-centric approach. This is a difficult task, it makes a structural guide set eligible. To prepare for next week’s AI Action Summit in Paris, I have placed three basic principles for the future of AI policy.

First, use science, not science fiction. The basis of scientific work is the main dependence on experience and strict research. The same approach should be applied to the AI ​​administration. Future situations capture our imagination-euopia or apocalips-functional policy maker claim a clear eye outlook on the current reality.

We have made significant progress in the recognition of the image and the processing of the natural language. Chatbots and co-pilot software assist programs are converting to work in exciting ways-but they are applying advanced data learning and pattern generation. These are not the form of intelligence, including the purpose, free will or consciousness. It is critical to understand, to protect our far -reaching situations and to focus on our important challenges.

It is not always easy to concentrate on the complications of AI, even to our reality. To fill the interval between scientific progress and real-world applications, we need equipment that will share accurate, up-to-date information about its capabilities. Established institutions such as the US National Institute of Standards and Technology can illuminate the real-world impact of AI, which leads to specific, functioning policies based on technical reality.

Second, become realistic than ideological. Despite its rapid progress, the field of AI is still in childhood, its biggest contribution. This is, principles about what and what cannot be made to reduce the involuntary consequences when encouraging innovation must be practically made in practical.

For example, use AI to more accurately diagnose the disease. It is likely to have a rapid democratization of high quality medical care. Nevertheless, if not properly managed, it can further enhance the bias present in today’s healthcare systems.

Developing AI is not an easy task. It is possible to develop a model with the best purpose and can be abused later for that model. The principles of the best administration will be strategically designed to reduce this national risk while awarding responsible implementation. Policymakers must create practical responsibility policies that discourage deliberate abuse without unjustly punishing the efforts of good-faith.

Finally, empower the AI ​​ecosystem. The technology can inspire students, help us to take care of our old age and solve innovation for cleaner energy – and the best innovations come through cooperation. So it is even more important that the policy makers empower the entire AI ecosystem, including the Open Source Community and Academia.

Open access to AI models and to equipment to equipment is important for progress. It will create obstacles and slow innovations, especially for academic institutions and researchers who have lower resources than the private sector parts. The consequences of this national limit must extend beyond academia. If today’s computer science students cannot conduct research with the best models, they do not understand these complex systems when they enter the private sector or find their own companies – a serious gap.

The AI ​​Revolution is here – and I’m excited. In the AI-powered world we have the potential to improve the human condition dramatically, but to make it a reality, we need administration that are deeply involved in experienced, associates and human-centered values.