April 29, 2019 | Written by: Mary Reisert
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We’re excited to kick off a new series for the Watson blog, focused on the people behind IBM Watson. To kickoff the series, meet Distinguished Engineer Bill Higgins.
You recently joined the IBM Watson team. Can you tell us about your previous background and what interests you about AI?
I’ve worked at IBM my whole career since graduating from Penn State in 2000 with a computer science degree. I spent my first ten or so years on various aspects of development, but in the past five years, I’ve been focused on various aspects of enterprise transformation—that is, how do we help a company like American Airlines, or BNP Paribas, or IBM for that matter—modernize to better serve customers by making use of better practices and supporting technologies. For instance, a few years ago I led an internal initiative to overhaul IBMers’ approach to development via social coding and better interdisciplinary collaboration, supported by tools like GitHub Enterprise and Slack. Ask anyone in development, and they’ll tell you it’s a different company vs. just a few years ago.
So, while I am not an AI person, I approach AI through the lens of transformation. That is, while AI represents a significant paradigm shift, at some level it’s just “a powerful new tool” and as my friend Grady Booch says, “a fool with a tool is still a fool.” I think about AI first from a human learning perspective—how can we help people learn why, when, for whom, and how they should use this tool such that it leads to better outcomes.
What are you looking to accomplish in your new role?
Right now, for most people and companies, they’re at an “indistinguishable from magic” level of understanding. I think it would be a good thing for the world if we demystified AI and gave both executives and developers a conceptual and technical framework from which they could intelligently make AI a part of their approaches to ongoing enterprise transformation and development. If I’m able to make a big contribution to that, both for IBM’s clients and IBM itself, I’ll be satisfied.
Can you tell us about your team and what they’re working on?
My team directly supports the two goals above. The first thing is that we evolve IBM’s fundamental AI capabilities like language, speech, and vision, and then provide a developer experience composed of SDKs, other tooling, documentation, and APIs, that make them accessible to developers. The second thing is that I have a small sub-team that plays a leadership role in a company-wide guild where we are working on an accelerated, scalable approach to help companies, including IBM itself, infuse AI in their applications and business processes.
For people interested in AI but aren’t sure where to begin, what would you recommend that they do to get started?
I see people make two common mistakes with AI: 1) thinking it doesn’t apply to them and/or 2) not understanding the sorts of use cases for which AI is superior to traditional techniques. To avoid those two mistakes, I would like to ask folks to invest some time in understanding AI fundamentals—what it is, how it works and when it tends to be better than traditional techniques. Then explore how people are using AI in your domain or industry or domain today. There are a wealth of resources on both, and a few hours of Google-searching and link-following will give you a good grounding. In the coming months, we will articulate IBM’s point-of-view on these topics through new content on the IBM Garage Method’s new “Reason” section, so keep your eye on that.
Discover how you can start your own AI journey with Watson.