This week on The Digital Life, we discuss the pitfalls of predicting AI. AI predictions range from the measured and meaningful to highly unrealistic and downright hysterical. But how can you tell the difference? In this episode, we dig into some rules of thumb for thinking through the AI predictions we encounter, as laid out in the article “The Seven Deadly Sins of AI Predictions” by Rodney Brooks, a founder of Rethink Robotics. From better understanding the properties of narrow AI to asking “how will it be deployed?”, questioning supposed magical properties without limit, to admitting, in the long term, we just don’t know, we’ll explore the many factors that counter the breathless hysteria of AI predictions. Join us as we discuss.

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The Seven Deadly Sins of AI Predictions

This week on The Digital Life, we explore the difficulties of establishing an AI code of ethics, inspired by an article from MIT Technology Review, “Establishing an AI code of ethics will be harder than people think”.

There’s already ample evidence that artificial intelligence can exacerbate existing system bias if left unchecked. And, a set of design ethics guiding AI development may be far in the future, as the difficulty of defining an applicable rule set, and the subjective nature of ethics itself, makes the task extremely difficult. However, such arguments over AI ethics often emphasize top-down efforts rather than bottom-up — for instance, auditing AI decision-making from the initial data curation stage and throughout the process. In this view, AI design and development is not a purely technical practice, but instead incorporates cultural aspects, similar to teaching children right and wrong. Join us as we discuss.

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Establishing an AI code of ethics will be harder than people think

This week on The Digital Life, we discuss the intersection of artificial intelligence and science with special guest is Dany DeGrave, founder of Unconventional Innovation. AI and science are coming together in new and significant ways, including the use of cognitive and other innovative technologies in R&D — like NLP, machine learning, and advanced analytics. As bio-science companies rush to invest in AI, the implementation of scientific research, drug trials, and even personalized medicine is undergoing significant change. But with the potential to make erroneous decisions, and even be used for malicious purposes, it may be a long time before we fully trust AI to be used in such development.

This week on The Digital Life, we speak with special guest, Jason Grant, CEO of Integral, about human development models and the role of human development in creativity.

On The Digital Life this week, we chat about synthetic biology and the new categories of emergent life that will result from its practice. The work of synthetic biologists is changing the way that life evolves. How can we sort through the new categories of life that will be designed by humans, not necessarily evolved through natural selection? And what is the nature and role of digital information — genetic data that will now define a blueprint of a newly designed life form? Join us as we discuss.

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If we made life in a lab, would we understand it differently?