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Bridging or widening? Generative AI’s impact on the racial wealth gap

todayJanuary 17, 2024

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Bridging or Widening? Generative AI’s Impact on Racial Wealth Divides

A major economic shift is underway. Generative AI—technology that can generate new data, text, code, images, and more from vast data sets—stands poised to drive up to $4.4 trillion in global economic impact within the decade. Leaders across industries are waking up to generative AI’s nearly limitless potential to transform how work gets done. But could this transformative technology also help dismantle longstanding barriers to economic inclusion like the racial wealth gap?

A new McKinsey report offers reason for hope—and urgent concern. Without thoughtful implementation, generative AI threatens to exacerbate racial wealth gap. But equitably deployed, it could also accelerate progress across healthcare, education, finance, and other key pillars of economic mobility for Black Americans closed off from opportunity. The choices leaders make today in shaping this transformation will reverberate for generations. There is no time to lose in charting the course toward an inclusive AI future.

Racial Wealth Divides at Risk of Widening

Generative AI’s rise comes at a moment of stark racial inequality. The typical Black family in America holds just $44,000 in household wealth—one-sixth the assets of the typical white household. This economic chasm traces back to the evils of slavery and the enduring structural barriers to wealth-building that followed, from Jim Crow to modern-day discrimination in housing, banking, and beyond.

As a core engine of future economic growth, generative AI could widen these divides even further if existing disparities remain unchecked. Experts project nearly $500 billion in new household wealth in the U.S. alone by 2045 as generative AI unlocks new value and productivity gains. However, if Black households receive only proportional benefits, the racial wealth gap would grow by a devastating $43 billion per year—hardly the future so many social justice advocates envisioned.

Bridging or Widening? Generative AI’s Impact on the Racial Wealth gap

Pathways to Mobility Under Threat

Generative AI also risks hollowing out “high mobility” jobs that have offered stepping stones to the middle class for Black workers without college degrees—the vast majority. Nearly a quarter of Black workers are employed in roles facing over 75% likelihood of automation from generative AI versus just 20% of white workers, per McKinsey.

Customer service, production, and administrative assistant positions could see significant impacts. Indeed, up to half of the “gateway” and “target” jobs accessible to Black workers could be transformed by new AI capabilities over the next two decades. Even training programs in fields like IT that lead to higher-paying roles appear vulnerable, as generative AI can now write basic code and may soon automate entry-level software engineering jobs.

The upshot is the loss of on-ramps to economic stability and mobility for Black workers precisely when racial progress remains so urgent. But what if generative AI could help remove barriers to inclusion and shared prosperity instead?

Choose Inclusion: Leading Generative AI Toward Equity

The McKinsey report maps out how leaders across healthcare, education, finance, and other pillars of mobility can steer generative AI toward inclusive ends—if they act now.

Healthcare Inequities Demand Innovation

Generative AI promises powerful healthcare access and quality advances for marginalized communities facing alarming care and outcome disparities—but only if equity is baked into system design.

Consider maternal health. Black women still face appalling gaps in mortality and complications compared to white mothers. Advanced generative AI analysis of patient health records could flag risk factors early and prompt interventions, lowering mortality by up to 70%. Or take medication adherence, where personalized AI care plans and prescriber guidance could drastically improve outcomes for Black patients lacking regular treatment for chronic conditions.

However, the risk of harm still lurks if biases infect medical AI. One infamous algorithm demonstrated racial bias against Black patients in prioritizing care—a danger when medical AI increasingly drives decision-making. Careful audits and representation in data/development teams are vital.

Financial Inclusion Still Lacking

Over 40% of Black households today sit outside the traditional banking system, forced to rely on predatory services like payday lending. Yet most want access to affordable financial tools for stability and mobility.

If focused on real needs, AI could also prove transformative in connecting excluded communities to mainstream banking. Personalized AI marketing and automated financial advisors can provide tailored planning for saving, building credit, and wealth creation within communities banks have historically ignored. Fintech lending algorithms trained on ethically sourced data can help counter structural denials of mortgage and small business lending.

Affordable Housing Scarcity Compounds Inequality

With homeownership a vital pillar for family wealth building, the 30-point Black-white racial gap in US homeownership feeds devastating inequality. Housing discrimination persists, but AI tools could significantly improve access and affordability if thoughtfully implemented.

AI-optimized financing models can ethically broaden access to credit and help first-time buyers overcome barriers like student debt. Predictive sales data can steer developers toward underserved neighborhoods where new mixed-income housing is most needed. Automated remote housing inspections utilizing computer vision could significantly lower development costs.

However, safeguards must counteract AI that has denied housing based on race or incorrectly assessed predominant minority neighborhoods as riskier investments. Like in healthcare, representativeness, transparency and auditing matter tremendously.

Targeted Education Interventions

Achievement and funding gaps in schools disproportionately impacting students of color could widen with tech-enhanced personalized learning—or narrow if equity is prioritized in design.

For example, adaptive AI tutoring tailored to individual needs shows promise in tackling literacy divides if focused squarely on accelerating marginalized learners. Implicit bias detection in AI algorithms scoring essay exams helps teachers give fairer feedback.

However, students lacking home broadband access or devices can’t utilize AI-boosted remote learning tools that require connectivity. Leaders must confront digital divides for innovative ed-tech to uplift all talent.

Confronting the Digital Divide

As generative AI increasingly powers vital services online, digital exclusion carries heavy consequences. Yet Black Americans face disproportionate barriers to affordable broadband access and device ownership, fueling participation gaps.

A significant digital divide persists, with around 40% of Black American households lacking access to high-speed fixed broadband, compared to only 28% of white American households that face this connectivity barrier.. Closing these divides is an urgent first step in enabling equitable access to AI-enhanced tools for health, jobs, education, and beyond.

Generative AI itself could help increase accessibility if focused on the problem. AI digital assistants tailored for underserved groups spread information and refer users to support programs. Network coverage gaps in marginalized communities can be algorithmically identified and prioritized.

But much hangs in the balance. As companies and governments rush to deploy generative AI augmenting consumer and citizen services online, we risk cementing a bifurcation where digitally disconnected communities lose touch while the privileged accelerate ahead.

Bending the Arc Toward Inclusion

The choices leaders make today in steering generative AI will reverberate for marginalized communities for decades to come through compounding effects.

Only urgent, decisive efforts baking equity into developing systems can ensure Black Americans and other disadvantaged groups aren’t structurally excluded from accumulating social and economic dividends in the AI age. A reckoning is here, as society again stands at a familiar precipice—will technology lift up shared prosperity or entrench inequality?

Story written with assistance from Claude AI

Written by: Tarik Moody

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