Based on my proprietary frameworks, in building artificial intelligence ecosystems there are 8 stakeholders that effectively connect as a value network. While government policy and advocates will call to increase diversity of talent by lowering the barriers of participation for all regardless of organizational affiliation, this is a recipe for disaster.

If this happens, it means we are removing educational merit if we want security, and accountability. My frameworks redesign the entry marging / the entry barrier to Artificial intelligence (and other technologies) not lower the barrier. The existing barrier to PETs adoption can be solved by redesigning the entry barrier for each stakeholder.

In my experience as a World Economic Forum artificial intelligence and entrepreneurship expert, I believe there’s a demand for a whole generation of workers skilled in technology. These technologists must emerge from innovation ecosystems. There are systematic, structural and institutional barriers that many times and almost always limit opportunities that are also applicable to PETs. Once we identify the attributes of each innovation ecosystem, we can use artificial intelligence to identify the specific barriers affecting PETs.

We can’t generalize or compartmentalize the barriers. Successful innovation ecosystems that we know of in Boston, Silicon Valley, and Seattle all have educational merit. Why? Because they are anchored by the most successful entrepreneurs and ventures in the world.

Innovators from underrepresented backgrounds and underserved communities do not have a pathway to achieve their innovation goals. Capital is not the barrier in these ecosystems. It’s the lack of intellectual infrastructure in the region that’s the main barrier. Using advanced technology and artificial intelligence, we can identify the attributes of each community. Generalizing the results is doing a dis-service to the community. And relying on human knowledge alone does not do the work / results justice.

Using a software layer, the US Federal government must identify the stakeholders who are eligible to participate in the innovation ecosystem. Think of those “eligible” as the “total addressable market.” From this pool of eligible stakeholders, we identify those who have shown a willingness to become entrepreneurs, innovators, or technologists using various artificial intelligence methods that we can identify. To provide context, a Harvard Business School professor’s definition of entrepreneurship is “the pursuit of opportunity beyond resources controlled.” In this case, my definition of underrepresented, underserved, or marginalized is an individual or group who has knowledge and education of the said technology or innovation but lacks the intellectual infrastructure to realize their goals. The education component is critical because everything we do, must have educational merit. If our targets are truly innovators/technologists, these stakeholders must have educational merit. We are not expecting them to have all the knowledge, but should have access to the intellectual infrastructure. Using artificial intelligence, we can identify those most likely to succeed innovators/technologists and unlock their potential to succeed. Unfortunately, using human knowledge alone to realize this goal is difficult.

Entrepreneurs/technologists from marginalized groups and underserved communities all exist / live in communities with community colleges, technical schools, vocation schools, colleges, universities, and high schools. Using technology and a software layer, we can leverage these institutions to identify the specific barriers. But we must “redesign the entry barrier” so that these stakeholders (innovators or specific user type) understand “how” to achieve their goals, otherwise, they won’t have the willingness to share and engage. Again, we can’t “lower” the barrier to engage, because that won’t have educational merit, we must redesign the barrier.

I will reinforce again that capital is NOT the barrier for marginalized or underserved innovators to achieve their goals. If we throw capital at the problem, but the intellectual infrastructure does not exist, then we don’t achieve our goal. Let us use technology and artificial intelligence to solve this problem, redesign the entry barrier for stakeholders, and build a pipeline of
innovators so they are no more underrepresented, underserved, or marginalized. Our goal is to have upward mobility for each of these stakeholders so that they are no more identified as such.