Three Things I Learned: Living with AI (Experts)

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Credit: Tanisha Bassan

There is strong evidence to show that subject-specific experts frequently fall short on their informed judgments. Particularly when it comes to forecasting.

In fact, in 2005 the University of Pennsylvania’s Professor Philip E. Tetlock devised a test for seasoned and respected commentators that found as their level of expertise rose, their confidence also rose – but not their accuracy. Repeatedly, Tetlock’s experts attached high probability to low frequency events in error, relying upon intuitive casual reasoning rather than probabilistic reasoning. Their assertions were often no more reliable than, to quote the experimenter, “a dart throwing chimp.”

I was reminded of Tetlock’s ensuing book and other similar experiments at the Future Trends Forum in Madrid last month; an event that (valiantly) attempts to convene a room full of thought leaders and task them with predicting our future. Specifically, in this case, our AI future.

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Tech for Humans, Part 2: Designing a Human-Centered Future

YouTheData.com is delighted to feature a two-part guest post by Andrew Sears. Andrew is passionate about emerging technologies and the future we’re building with them. He’s driven innovation at companies like IBM, IDEO, and Genesis Mining with a focus on AI, cloud, and blockchain products. He serves as an Advisor at All Tech is Human and will complete his MBA at Duke University in 2020. You can keep up with his work at andrew-sears.com.

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In Part 1 of this series, we explored the paradox of human-centered design as it is commonly practiced today: well-intentioned product teams start with the goal of empathizing deeply with humanneeds and desires, only to end up with a product that is just plain bad for humans.

In many cases, this outcome represents a failure to appreciate the complex web of values, commitments, and needs that define human experience. By understanding their users in reductively economic terms, teams build products that deliver convenience and efficiency at the cost of privacy, intimacy, and emotional wellbeing. But times are changing. The growing popularity of companies like Light, Purism, Brave, and Duck Duck Go signifies a shift in consumer preferences towards tech products that respect their users’ time, attention, privacy, and values.

Product teams now face both a social and an economic imperative to think more critically about the products they put into the world. To change their outcomes, they should start by changing their processes. Fortunately, existing design methodologies can be adapted and augmented to build products that appreciate more fully the human complexity of their users. Here are three changes that product teams should make to put the “human” in human centered design:

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Making AI in our own image is a mistake

This article by Fiona J McEvoy (YouTheData.com) was originally posted on All Turtles.

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When the Chinese news agency Xinhua demonstrated an AI anchorperson, the reaction of the internet was predictably voluble. Was this a gimmick or a sign of things to come? Could the Chinese government literally be turning to artificial puppets to control the editorial content of the country’s news channels? Are we careening towards a future where the humans and humanoid bots are indistinguishable?

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AI and the future shape of product design

This article by Fiona J McEvoy (YouTheData.com) was originally posted on All Turtles.

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These days we talk so much about artificial intelligence and its creators that it’s easy to overlook the increasingly prolific role AI itself is playing in product creation and design. Across different industries, the technical and the creative are being drawn closely together to create a range of products that may otherwise never have been conceived.

Blowing past the wind tunnel

Take, for example, the new aerodynamic bicycle presented this month at the International Conference on Machine Learning, which was designed using Neural Concept software. By employing AI in the design phase, a small team from French college IUT Annecy were able to completely bypass the usual methods of testing for aerodynamism – a process that usually requires a great deal of time and computing power.

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