Beneficence, the principle of doing good, complements the ethic of nonmaleficence—do no harm. Beneficence is a call to serve the common good rather than the interests of a select few.
In the context of artificial intelligence, beneficence is a sustained commitment to ensuring that AI benefits all of humanity and the environment. Examples include enhancing individual and public health, promoting human flourishing, achieving peace and understanding, creating socio-economic opportunities, and fostering economic prosperity, especially for vulnerable populations. These aspirational examples illustrate the extraordinary power and potential that AI has in every sector of society, which comes with tremendous responsibility.
A central ethical objective is ensuring that technological advancements benefit all humanity, sentient beings, and the planet. Instead of symbolic corporate statements, responsible developers view beneficence not as marketing rhetoric but as a way of life—a way of doing business at every stage of the AI lifecycle. This commitment to generosity and stewardship accelerates technology’s economic value while elevating human dignity and ecological sustainability, in alignment with the UN Sustainable Development Goals.
Leaders in the tech-for-good movements align profit objectives with empowering communities and solving real-world problems, illustrating the wisdom of valuing the process as much as the product. By minimizing conflicts of interest, and creating reward systems for selfless behavior, AI technologies will contribute positively to society, enhance human capabilities, and promote collective well-being. Their practical strategies include creating business metrics to assess AI’s impact on quality of life, such as health, happiness, justice, or access to economic opportunities.
In doing so, these leaders exemplify the ethical development of AI, by maintaining a lifelong commitment to mitigate harm and advance the common good.
For Further Reading
Anna Jobin, Marcello Ienca, and Effy Vayena. "The Global Landscape of AI Ethics Guidelines." Nature Machine Intelligence 1 (2019): 389–399.
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