Report Summary: The impact of generative AI on Black communities
A new report by McKinsey on the impact of Generative AI on Black communities highlights both the potential risks and opportunities of this transformational technology. It's a worthwhile read for anyone interested in ethical and equitable AI. Here's our summary.
Key Risks:
Gen AI could widen the existing racial economic gap in the U.S. by $43 billion annually
Black workers are overrepresented in roles most likely to be impacted by automation
GenAI may simultaneously disrupt “gateway” jobs that are a key pathway for upward mobility – even those pathways previously considered “future-proof” like software engineering
Embedded bias in AI solutions and lack of access to GenAI tools are poised to exacerbate unfair outcomes and inequality (this can be recently seen in the class action suit and against RiteAid on their use of biased facial recognition software).
Opportunities:
A greater focus on the development of future-proof skills – those that require a high degree of emotional intelligence, skills that require hand-eye coordination and someone's physical presence, and nuanced problem solving
GenAI has the potential to expand access to personalized healthcare solutions and financial inclusion, areas in which black communities have faced significant exclusion
What this means for K12 education:
On one hand, GenAI can be implemented to improve personalized instruction in underfunded schools that disproportionately serve minority student populations. Or those schools lacking resources to adopt expensive GenAI tools may end up at an even greater disadvantage than they currently are.
Ultimately so much depends on the responsible development and deployment of this technology.
McKinsey highlights 3 key ways to ensure a more equitable future:
1. Vigilant Implementation: Prepare workers for a post-GenAI world, focusing on re-skilling in foundational and transferable skills, and using GenAI in appropriate contexts that do not exacerbate inequalities.
2. Building Responsible AI: Develop Gen AI with diverse data sets to lower algorithmic bias and involve diverse stakeholders in the design, development and deployment process.
2. Sustaining Responsible AI: Establish regulations to limit the negative impacts of GenAI on diverse populations and ensure equitable access to best-in-class tools to avoid a new digital divide.
Studies like these are incredibly important to ensure that GenAI is a force for good and we hope to see technology companies and regulatory bodies adopting these mitigation strategies.
Here's a link to the full study.
