A Proposal to Democratize AI

To ensure AI fulfills its potential, we must democratize the technology to avoid allowing it to be yet another driver of inequality. Here’s how we start.
Headshot of author Ben Lamm
Ben Lamm
Expert Contributor
October 27, 2020
Updated: October 28, 2020
Headshot of author Ben Lamm
Ben Lamm
Expert Contributor
October 27, 2020
Updated: October 28, 2020

COVID-19 has exposed the gaping income inequality that plagues America. Access to and the ability to engage with technology exacerbate these gaps even further on both the individual and the corporate level. As AI makes companies more efficient and eliminates the need for some types of jobs, wealth will continue to collect around small pockets of people and leave others behind. We know that the top 1 percent of the wealthiest people captured 95 percent of income growth from 2009 to 2012. Currently, I see little evidence of a shift in this ongoing economic consolidation. This is not the world I want to live in.

As innovators, I believe we have a responsibility to do everything we can to ensure our companies and products solve the problems society faces instead of exacerbating them. Given that I run an AI company, I have seen firsthand the massive advantages that well-capitalized companies gain when they integrate artificial intelligence solutions into their businesses. And similarly, I can see how local coffee shops, neighborhood restaurants and other small businesses will be left behind. If we want to create a more equitable world, and I do, we must address the growing artificial intelligence gap. The pathway to do so is simple: better AI education, better understanding of data capture and governance and more democratization of access to AI.

Data is the heart of artificial intelligence. The data may pertain to personal shopping habits, business operations, historical patterns or any number of other areas. The fascinating thing is that there are millions of receptors collecting volumes of data on our smallest actions. Most of us don’t know what information is being captured, why it’s important or what we can learn from that data. To achieve truly revolutionary technology solutions, we need broad swaths of people across all disciplines to understand, engage with and use data.

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Improving AI Education in Schools

The path to a better future must start with childhood education to increase data literacy. That curriculum should address what data means, how it affects society and how anyone can use it in their day-to-day lives. We must train students in this way as soon as they enter school for maximum effect. If we understand data inherently from a young age, we can interact with it confidently as we move forward in our lives and careers. Data literacy is a fundamental stepping stone to understanding artificial intelligence. And with the global economic impact of AI expected to reach nearly $16 trillion by 2030, understanding AI is paramount to securing the jobs of the future. A solid knowledge base will allow students to move across all sectors and levels of the business world when they leave school and enter the economy.

An article from We Are Teachers shares that “At Montour Public Schools in Montour, Pennsylvania, Justin Aglio, director of academic achievement and district innovation, believes every student should have exposure to AI. Montour’s AI program first started in the fall of 2018, but not as an isolated course. Rather, infusion of AI education happened across the curriculum in math, science, music, and library classes.” The Montour program is an excellent model for an AI curriculum. AI training shouldn’t just be a standalone computer science course. Instead, like the internet, it needs to infuse all subjects. To improve AI education in our school systems, we must upskill teachers so they can understand and explain the complexities of data to students starting from a young age. Doing so will require federal funding to subsidize training teachers across America in AI. Although such a program is unlikely in our current political moment, it is still a necessity. While we’re at it, perhaps we can also increase their pay and improve access to technological devices for students in underprivileged communities. I don’t know exactly how to make this happen, given the immensity of the challenge. Still, I’m hopeful that politicians and leaders from the tech and educational spaces can galvanize support for this idea. I’m certainly willing to do my part to help bring it to fruition.

We need learning tools that incorporate and also help to explain AI. We need teachers who can explain how businesses and other entities acquire and use data. And we need an education system that incorporates lessons about nascent technology so that students aren’t playing catch up when they enter higher education and the workforce. But we can’t base our hopes on education alone. The process is too long, and we’re already too far behind. We also need a population that understands the value of AI right now in order to build the political will necessary to ensure that schools have AI-integrated curricula. For that, we need to foster a more generalized understanding of artificial intelligence at a national level.

 

Improving the Publics Understanding of AI

Society’s understanding of AI is fragmented. A 2019 survey from the University of Oxford’s Future of Humanity Institute defined AI as “computer systems that perform tasks or make decisions that usually require human intelligence” and asked people for their feelings about such systems. The results were mixed: 41 percent of respondents said they somewhat or strongly supported the development of AI, while 22 percent said they somewhat or strongly opposed it. The remaining respondents said they had no strong feelings one way or the other or didn’t know. This popular confusion about embracing AI highlights the need for more education about what it is and how it works. AI literacy is not enough, however. As a nation, we must understand that AI is about data. And we must develop a better understanding of data accordingly.

Data literacy is important because it helps businesses to grow. Yet, according to the International Data Corporation, half of today’s companies don’t have a workforce capable of using AI to generate revenue. The only way to combat this is through training. That same IDC study noted that four out of every five companies need to launch specific programs targeting their employees’ shortcomings in data skills. Companies will increasingly be the central education hub on AI for their employees. As such, the government should incentivize companies to train their workforce on data literacy because it will help our country be more data literate as a whole and better prepared for future technical leaps.

The future isn’t about more technology; it’s about more intelligence. That means more computing intelligence, but also more human intelligence about how computer power works. To understand AI-based computing, we need to teach better data understanding. In the business world, a rudimentary understanding of AI results in wasted development time, failed and impractical implementation and unnecessary expenses. The broader misunderstanding of AI leads to fear-mongering and apathy about its potential in our society.

If we don’t improve understanding of data and its relationship to AI, our workforce will be prey to Hollywood stories of evil AI. Rather than having a sophisticated and calculated understanding of its uses, people will accept the pop-cultural vision of AI as a technological bogeyman. They may assume that we’re becoming victims to AI overlords, soon to engage in a battle for the very existence of the human race. People also might fear that AI will make human work obsolete, further exacerbating inequality. This fear obscures the fact that, in the future, AI could be humanity’s strongest tool.

 

Democratizing Access to AI

Finally, as we work to improve childhood education and raise national awareness, I look to the tech industry to provide solutions that will increase access to artificial intelligence and associated tools. Democratization of our technology helps to create more competitive businesses both locally and globally. As we see a potential economic downturn, we must confront the question of how we can create a better economy to compete abroad and to improve our lives at home.

Democratization reduces barriers to entry for individuals and organizations to start experimenting with AI. With easier access, people anywhere in the world can experiment with the technology with little to no financial outlay. Not only does democratization allow people to learn about AI and its uses, but they can also attempt to address problems in the marketplace. Such a scenario could eventually reduce the overall cost of building AI solutions as more people start manipulating the data, algorithms, and tools to build more powerful solutions.

Today, more than 500 providers offer AI services and solutions. Unfortunately, these tools are guarded by moats like lock-in models, expensive pricing and the difficulty of customization without highly technical expertise. Although this model is lucrative for the businesses themselves, it’s harmful for society at large because it accelerates trends around unequal access and threatens to leave even more people and businesses behind.

Data from Forbes reveals that startups using a digital-first strategy driven by AI adoption increase their revenue by an impressive 34 percent. Although adoption is clearly lucrative, it is often too costly, difficult or complicated for many companies to make the necessary investment. These issues make the incorporation of AI nearly impossible for smaller, less-well-funded companies. To democratize AI, we need fewer moats.

To allow for the universal implementation of AI, we must create an easier means of engaging with the growing technology. Currently, many businesses don’t have a way to pick the right services that can help them create, deploy and then operate AI-based business solutions. The only way to adopt an AI-first approach to business is to leverage a solutions company that can help integrate and scale a solution. For many companies, that moat is just too deep.

In the early days of the internet, web design and service providers built a similar moat. They built and sold websites at premium prices to companies that had the capacity to engage online. Those companies were able to take advantage of early technical opportunities to grow market share and create monopolies. As the internet became democratized, however, more and more companies were able to move aspects of their business online. This diversification became more important as economic downturns and pandemics have changed the ways we shop, buy and otherwise connect with businesses.

Now, nearly anyone can start and run an online business using a few simple tools like Wix and Squarespace. In the future, AI tool adoption and implementation should be just as easy. We need the baker down the street and the small business next door to be able to compete with the behemoth businesses of our time. This means that they have access to and can take advantage of the same competitive tools whenever and wherever they want to.

If we are able to improve education, raise national awareness and democratize access, I believe we will be well on our way to bridging the gap between the haves and have nots. And we can ensure that our technology reduces that gap rather than widens it.

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