Muse Health challenges our partners to deploy Gen AI with an equity lens. Leaders find themselves at a pivotal moment with Gen AI: they can harness its potential to promote inclusion, fairness, and opportunity, or they can allow its evolution without paying particular attention to equity and societal implications. Leaders developing Gen AI strategies for their organizations can consider using their influence to raise awareness of the technology’s potential impact on equity in the following ways:

Muse is committed to vigilant implementation:

1. Reskilling workers: Workers at risk of displacement by Gen AI can undergo training in skills that are less susceptible to technological replacement in the near future and are transferable across various roles. This involves emphasizing foundational and nuanced skill development over role-specific training.
2. Judicious use: Leaders and organizations implementing Gen AI must ensure its deployment in contexts where it can reliably and fairly make decisions. It should not be used where understanding nuance or considering cultural, historical, or social factors is crucial, or where complex, high-risk questions need careful framing and resolution.

Muse is committed to sustaining responsible Gen AI:

1. Regulation: Lawmakers and regulators should continuously monitor new and increasingly common applications of Gen AI across industries and functions to prevent its misuse, particularly in ways that may harm Black and other marginalized communities. Establishing “rules of the road” can ensure that companies using Gen AI protect sensitive data from being compromised and misused.
2. Democratized access: Gen AI should be equally accessible to all individuals. Broadening its user base fosters new, creative, and meaningful applications while preventing the creation of a digital divide. Additionally, digital literacy programs should incorporate Gen AI into educational curricula for all students.

Muse believes in responsible Gen AI:

1. Nutritious data: Training foundation models on unbiased, authentically representative data sets devoid of racial, ethnic, gender, or other biases ensures that Gen AI products generate fair, accurate, and reliable outputs.
2. Diverse tech talent: Promoting and nurturing a diverse pool of Black and other underrepresented tech talent ensures that Gen AI is developed and guided by a broad range of perspectives, experiences, and understandings of its impact and potential.
3. Participatory design: All stakeholders, including end users and those affected by new applications, should participate in the design of Gen AI products to ensure their relevance and effectiveness.