How AI Might Impact Sustainable Development Goals

How can the EHSQ community contribute to the UN’s 2030 Sustainable Development Goals? One way is through strategic investment in AI. Find out the focus areas here.

In 2015, the United Nations established its 2030 Agenda for Sustainable Development to “provide a shared blueprint for peace and prosperity for people and the planet, now and into the future.” The 17 Sustainable Development Goals (SDGs) provide an actionable basis for participating countries to advance the SDGs through their local policies and initiatives. The 17 SDGs (that are associated with 169 more specific targets) are:

GOAL 1: No Poverty
GOAL 2: Zero Hunger
GOAL 3: Good Health and Well-being
GOAL 4: Quality Education
GOAL 5: Gender Equality
GOAL 6: Clean Water and Sanitation
GOAL 7: Affordable and Clean Energy
GOAL 8: Decent Work and Economic Growth
GOAL 9: Industry, Innovation and Infrastructure
GOAL 10: Reduced Inequality
GOAL 11: Sustainable Cities and Communities
GOAL 12: Responsible Consumption and Production
GOAL 13: Climate Action
GOAL 14: Life Below Water
GOAL 15: Life on Land
GOAL 16: Peace and Justice Strong Institutions
GOAL 17: Partnerships to achieve the Goal

Vineusa et al. (2020) took a look at how artificial intelligence (AI) might impact, support, or inhibit these development goals. The purpose of their work was to be able to highlight which of the 169 targets would benefit the most from investment and innovation in applied AI. For the purpose of the study, they considered all of these things to be under the banner of “AI”:

  • Perception—including audio, visual, textual, and tactile (e.g., face recognition),
  • Decision-making (e.g., medical diagnosis systems)
  • Prediction (e.g., weather forecast)
  • Automatic knowledge extraction and recognition from data (e.g., discovery of fake news circles in social media)
  • Interactive communication (e.g., social robots or chat bots)
  • Logical reasoning (e.g., theory development from premises).

AI Can Drive Positive Impact

They found that AI has the potential to drive significant positive impacts for ending hunger, promoting good health and well-being, advancing clean energy, building sustainable communities, and strengthening peaceful relationships between countries while building solid institutions. On the other hand, their analysis found that AI has the potential to significantly inhibit the push towards quality education for all countries, as well as ending poverty and ensuring clean water.

The results of the study indicated that AI was likely to have a negative impact on inequality. According to the study authors, “The growing economic importance of AI may result in increased inequalities due to the unevenly distributed educational and computing resources throughout the world.”

The results indicate opportunities for the EHSQ community to contribute to the UN’s 2030 Sustainable Development Goals by focusing applied AI work on promoting worker health and well-being, improving sanitation, and building a more sustainable world by applying quality improvement techniques to promote EHSQ outcomes.

Additional Resources:

United Nations (UN). (n.d.) Sustainable Development Goals. Available from

Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., … & Nerini, F. F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 1-10. Available from

About the Author: Nicole M. Radziwill, PhD, MBA, is SVP, Quality and Strategy, at Ultranauts. She is a Fellow for the American Society for Quality (ASQ) , and editor for Software Quality Professional.

This entry was posted in Environmental & Sustainability Management and tagged by Nicole Radziwill. Bookmark the permalink.

About Nicole Radziwill

Nicole Radziwill is a quality manager and data scientist with more than 20 years leadership experience in software, telecommunications, research infrastructure, and higher education. Prior to joining Intelex, she was an associate professor of data science and production systems at James Madison University, Assistant Director for End to End Operations at the National Radio Astronomy Observatory (NRAO), managed software product development for the Green Bank Observatory (GBO), and managed client engagements for Nortel Networks and Clarify (CRM). She is an ASQ-certified manager of operational excellence (CMQ/OE), an ASQ-certified Six Sigma Black Belt (CSSBB), and contributed to the development of ISO 26000—“Guidance on Social Responsibility.”

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