Emerging Technologies

How to build the next generation of AI talent


Starting the journey into AI. Image: UNSPLASH/Michael Fousert

Joseph Wehbe
Chief Artificial Intelligence Ecosystem Builder, DAIMLAS
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Artificial Intelligence

  • Building a pipeline of AI talent and projects requires technical as well as educational merit. For this, AI centres of excellence led by world-renowned scientific advisors are necessary.
  • Stronger AI ecosystems emerge when government to grassroots initiatives get involved.
  • AI ecosystems materialize as value networks. They redesign the entry margin for stakeholders to start their journey into AI, offering them a path to participate.

The benefits of artificial intelligence as a catalyst for economic growth are distributed unevenly across cities around the world. Consequently, so is its talent. The AI hubs that we know of in Boston, Silicon Valley, Toronto (and so on) don’t exist in the heartland of the United States or in emerging or frontier markets globally.

These AI hubs are all anchored by some of the greatest learning institutions in the world, led by scientific advisors who attract global talent. Without such an AI ecosystem, you will not be able to build the next generation of AI talent.

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In AI development, while technology and algorithms have been commoditized, skilled workers that are able to create solutions to AI problems are the most important factor. There is a demand for a whole generation of workers with capacities in artificial intelligence. This will be the generation of talent that will support national interest in aerospace, defense, education, housing, transportation, public safety, supply chain, manufacturing, and many other industries critical to the nation's safekeeping.

Supporting the next generation of AI talent now

As John F. Kennedy put it: "Fix the roof when the sun is shining." And by all indications, the sun is shining on American AI achievements.

Simultaneously, to maintain this lead, it’s time to build the next generation of AI talent now. The United States of America is the global leader within the field of artificial intelligence as it relates to publications, capital invested, conference citations, net new funded companies, and patents accepted, according to Stanford University Artificial Intelligence Index Report 2022.

If we set the States as the northstar for AI ecosystems, we can identify opportunities for emerging tech hubs to grow their local ecosystems, too. According to Stanford University Artificial Intelligence Index Report 2022, the US Government spent the highest amount on AI contracting at the Department of Defense in 2021, and the lowest at the National Science Foundation (NSF).

Role of national governments

National governments need to contribute to grassroots AI ecosystem. Each stakeholder in an AI ecosystem adds to build a value network from the local government up to federal policy. An AI ecosystem is comprised of eight stakeholders that all have different goals. For these stakeholders to achieve their goals, they require government support.

The role of national governments specifically starts in providing recognition to AI degrees and education immediately at the graduate school level, but also in the k-12 curriculum. Imagine if government departments of education don’t recognize medical, legal, or teaching degrees? The education system wouldn’t function. But the paradox is that departments of education require to build internal expertise to be able to recognize such AI degrees.

The AI ecosystem and the approach to building the next generation of AI talent, can’t be compartmentalized. AI workshops, certifications, and bootcamps have no educational merit. They don’t build practitioner level skills.

Why are AI talent development and AI degrees not treated with the same rigor and standards as medical or law degrees?

We must start with standardizing AI degrees – backed to AI centers of excellence that are all led by grassroot organizations. As entrepreneurs and stakeholders concerned with building the next generation of AI talent, we can’t wait for governmental action to build localized AI ecosystems.

We must build around the intellectual infrastructure that already exists in local academic communities. For AI education to be effective, centers of excellence that engage via an eight-stakeholder model must emerge out of those communities. This is a bottom-up approach to bring merit to education in AI.

The call to action now is to identify the voids in your local ecosystem as entrepreneurial opportunities to add value. As such, the technology and academic community in each region must coalesce to build their local AI centers of excellence.

But this must be done in an integrated manner with all stakeholders who are educated and believe in the technological capability of AI. This means engaging with industry to build trust to work on local problems that can be solved with AI.

Without education, we won't be able to lead within the field of artificial intelligence. This is why bringing merit to the academic system of the discipline is more than crucial.

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