AI to Reduce Wealth Inequality Created by…AI

AI to Reduce Wealth Inequality Created by…AI

Ninety-nine percent of us are providing the data to make the richest people in the world fabulously wealthy. And this inequality is growing. An increasing reason is technology: a winner-take-all market is emerging around massive data stores (Cambridge Analytica claimed to have 5,000 data points on each person in a database containing millions of voters), along with Artificial Intelligence to predict and influence our behavior based on this knowledge. Companies that leverage this technology are widening the inequality gap. In America, the top one percent including Jeff Bezos (Amazon), Mark Zuckerberg (Facebook), and Sergey Brin and Larry Page (Google), have more combined wealth than the entire middle class. Not surprisingly, many of the richest people head the richest companies, and many of those companies are making their money by applying artificial intelligence (AI) to free data they collect from almost everyone.

This feels like the antithesis of responsible AI. What can we do to reverse the trend? This post describes a proposed system, currently in ideation, to do so.

Regulatory controls usually come first to mind, including schemes to require greater transparency regarding—and possibly even remuneration for—the use of personal data. But such an approach is unlikely in today’s regulatory climate.

We propose an alternative that is based on existing proven models, and which requires no regulatory intervention, only consumer choice. Similar to the use of “green” packaging or buying only cruelty-free cosmetics, we propose a labeling scheme to clearly identify companies who, through their business practices, reduce wealth inequality, thereby creating a powerful incentive to do so.

Here’s how it works: As illustrated in the picture below: (1) the Wealth Equality Index (WEI, pronounced “We”) Foundation establishes a Wealth Equality Index that indicates the degree to which a company contributes to wealth equality. 

The WEI mechanism

The WEI index is very simple, as shown below: green is best and red is worst, with yellow representing an intermediate state. The WEI index represents who receives the wealth that a company creates. Note that this is not the same as the products that the company offers or sells, nor does it reflect benefit to the company’s employees.

When the WEI system is in place, consumers will understand that, by purchasing from WEI-green companies, they can help to reduce wealth inequality worldwide. This creates a powerful incentive for companies to be accredited as Green.

So what decisions does a company make that allow it to be ranked as WEI green? We propose that it participates in the WEI ecosystem, as shown below.

A critical player in the WEI ecosystem are (2) a number of “Sovereign Wealth” funds worldwide. These organizations pay a yearly dividend to residents of some geography, in recognition of community ownership of some resource. For instance, the Alaska Permanent Fund pays a yearly dividend to every state resident, reflecting Alaska’s oil resources. There are similar funds in many other regions, such as Texas and Norway. These funds share in common the fact that they distribute wealth equitably: based on only residency, they do not require that a citizen has discretionary income available for investment.


SW funds increase wealth equality. Additional funds can be created by citizens using mechanisms like an initiative, bypassing lobbyists and special interests that might oppose it.

Catalyzing the WEI ecosystem are (3) WEI-green VC funds, which consolidate investments from sovereign funds, and for this reason, can be accredited as WEI green or yellow (4). As they do now, these VCs (5) invest in companies. These companies are then accredited (6) to carry the WEI green or yellow label, which attracts consumers (7).

Once this mechanism is in place, it grows nonlinearly, as shown below:

This is a complex adaptive system, with multiple players who will be constantly adjusting to each others’ behavior. For this reason, mapping the mechanism with DI, and using machine learning to track individual interdependencies, is necessary to optimize its behavior.

Now we have a WEI ecosystem—with a mechanism, a yardstick, and a referee—that rebalances the flow of wealth, including that wealth generated by data and AI. And it gets even better. Because we are redistributing wealth (not income) the WEI virtuous cycle will continue to work even if AI eliminates jobs.

If you would like to learn more about the WEI foundation, please write to us, at

Chief Product Officer at | Website

Kamesh Raghavendra serves as the Chief Product Officer at The Hive, a venture fund and studio that co-creates startups focused on AI-powered applications in the enterprise. He funds, builds and launches ventures with a data-driven, AI-centric approach towards re-imagining business processes and rewiring trade & commerce between organizations.

He has co-created many ventures that augment, automate and amplify decision making in IT service management, datacenter services, robotic process automation, business process transformation and industrial design & operations.
Kamesh is also active in building ventures that govern information harvesting from data through automated data provenance and privacy-preservation. Previously, Kamesh served in a number of leadership roles at NetApp, and had a stint at Goldman Sachs trading mortgage-based securities during the cusp of the 2008 crisis.

Quantellia LLC | Website

Pratt has been delivering AI and DI solutions for her clients for over 30 years. These include the Human Genome Project, the Colorado Bureau of Investigation, the US Department of Energy, and the Administrative Office of the US Courts. Formerly a computer science professor, Pratt is a popular international speaker and has given two TEDx talks. Her Quantellia team offers AI, DI, and full-stack software solutions to clients worldwide. Previously a leading technology analyst, Pratt has also authored dozens of academic papers, co-edited the book: Learning to Learn, and co-authored the Decision Engineering Primer. Her next book: Link: How Decision Intelligence makes the Invisible Visible (Emerald Press), is in production. With media appearances such as on TechEmergence and GigaOm, Pratt is also listed on the Women Inventors and Innovator’s Mural. Pratt blogs at

Senior VP & Head of SAP Academy for Engineering at

Based in Palo Alto, Ferose heads the SAP Engineering Academy, whose mission is to create the next generation of engineers to solve some of the most complex problems in the world.
Formerly head of SAP SE’s Globalization Services unit, Ferose was responsible for enabling the global adoption of SAP products worldwide.
Ferose was also the Managing Director of SAP Labs India. Starting at the age of 33, he held this post for over five years during which he transformed SAP Labs India into an innovation hub. In 2012, the company was recognized as one of the “Great place to work” in India for the first time.
Ferose is the Chairperson on the Board of Specialisterne USA, a not-for-profit foundation with the goal to create one million jobs for people with autism and similar challenges. He is the founder of the India Inclusion Foundation, a nonprofit, aiming to bring the topic of inclusion at the forefront in India.
Ferose has co-authored a best-seller on people with disabilities, called GIFTED. He also wrote “Innovating the World: The Globalization Advantage” and “GRIT: The Major Story”.