“We should shift the goal of AI from creating pure undirected artificial intelligence to creating beneficial intelligence (…) so let’s start researching this today rather than the night before the first strong AI is switched on.“
Stephen Hawking. Reddit Science AMA Series, July 27, 2015.
I would first like to thank those of you who participated in the live AI session at Design Thinking 2021 this past month. Hope that the information and insights shared during our discussion were of value to everyone. I appreciate the positive reviews and the encouragement to keep moving in this direction. Some of you were interested in just understanding how to approach the subject, while others have been working on AI projects for years already and met in the hallway to continue the discussion.
The definition of ‘deep tech’ has evolved. Just for this discussion’s sake and in the context of this specific session, we can think of it as the set of technologies that are not directly developed for end user services. For instance, core research in quantum computing is set to foster pivotal advancements in computational thinking, which leads to game changing performance and capabilities in AI, unleashing new possibilities as a result.
Design wise, our work is driven by devising meaning. We look at benefits and drawbacks, opportunities and risks, and anything in between. These matters become quite tangible when architecting outcomes, which materialize when specific value happens to be created in the process.
That is different from just producing an artifact because we simply can. Design involves experimental undertakings as a deliberate practice. That was the reason behind positioning TOPP, Test Oriented Progressive Prototyping, in our session. TOPP’s concept is key to generating data, analytics, insights and decisions (learning and training in other words) in the realm of QXbD, Quality eXperiences by Design.
Value and quality are correlated. Both are evolving human considerations resulting from our experience with a given service doing some meaningful job for us. This thought applies whether the service is enabled by a conventional product or delivered as a pure play service as such. That statement remains true for physical, digital and hybrid solutions.
De-risking investments in advanced technologies and elevating the chances to succeed in the process can be best approached by ‘designing to value’ and, therefore, by being quality minded. It takes a purposeful human centric orientation, which is achieved by intersecting HCD (Human Centered Design) and HFE (Human Factors Engineering.) It makes not only sense, but it is of the essence in HCAI, Human Centered AI.
As discussed during the session at Design Thinking 2021, investing in ‘AI’s deep tech’ is a critical success factor, but not the only one. We now see a growing share of R&D being devoted to HCAI. System visualization, observability, explainability, intuitive programmability, ease of command and control… all being very relevant and the substance behind the list provided on page 24 in the presentation.
Trending-wise, that happens to be consistent across the board when looking at digital transformation projects. In a discussion with peers at MIT a couple of years ago, I learned that close to 50% of R&D is best devoted to human centric technologies, so that we can reap the benefits and make the most of digital solutions, which turns out to be instrumental to technological leadership. Our conversations at Design Thinking 2021 concurred.
I have made my deck available on the Design Thinking 2021 site, where those who registered for the conference have access to the event’s presentations. As usual, I have also posted a copy on my SlideShare and, this time around, the same file is also available from my LinkedIn profile. Glad to continue the conversation.
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