AI Ethics Wants AI To Spur The UN Sustainability Development Goals (SDGs) Though AI Might Go The Other Way

You can assuredly claim that Artificial Intelligence (AI) is spurring the attainment of the United Nations (UN) Sustainability Development Goals (SDGs).

Score a big plus one for this gallant use of AI.

Meanwhile, please prepare yourself for the ugly side of this.

Are you ready?

AI is also likely to undercut the revered SDGs and we need to keep a watchful eye to make sure that the deployment of AI as a positive catalyst is able to far exceed the contrary use of AI for undermining global sustainability.

Consider for a contemplative moment the AI-adverse underbelly. AI can readily slow down the pace toward the SDGs. AI can confound SDG efforts. AI can falsely soak up sustainability improvement resources with little or no viable return. Worse still, perhaps, AI can be used to block or reverse sustainability progress and take the world backward rather than forward on its bumpy path toward SDG realization.

It’s the classic dual-edged sword conundrum.

AI is inarguably a dual-edged sword.

Sometimes you live and thrive by the sword, but sometimes you can get cut down by the sword. For my coverage of the dual-use of AI, see the link here. In the specific use case of the UN SDGs, AI as a sword or tool needs stridently to be adequately managed and guided. The sunny side up is using AI to make sure that these vital global aims reach fruition. The other side is to prevent or mitigate AI that does the exact opposite and drags SDGs into a spiraling abyss.

All of this vividly illuminates the fact that AI Ethics is a cornerstone of all facets of AI. AI Ethics gets us thinking about what AI is used for and how it is deployed. There is a lot of AI that fails to meet any semblance of Ethical AI precepts. An ongoing battle is being waged to ensure that we have AI For Good and try to stop or at least assuage the equally rising AI For Bad. For my ongoing and extensive coverage of AI Ethics and Ethical AI, see the link here and the link here, just to name a few.

Let’s unpack what the UN SDG is all about.

We can then examine how AI is spurring the SDG’s effort. That is not the end of the story. Many pundits would stop at the point that the SDG tale of AI seems to be all roses and sunflowers. Realistically, we need to shine a light on the downsides of AI too. If we don’t do so, the equation can get out of whack that the AI For Bad exceeds the AI For Good when trying to ensure that the SDGs are fulfilled.

No time allows for having an AI head-in-the-sand posture by any of us.

Fundamentals Of The UN SDGs

In 2015, the United Nations adopted a plan known as The 2030 Agenda For Sustainable Development.

This was intended to be a shared blueprint to encompass peace and prosperity for people throughout the globe and to foster better use of the planet. Worldwide participation was envisioned as the only substantive means to help end poverty, end world hunger, and end or demonstrably reduce other global suffering and deprivations. All told, the plan was the culmination of decades of deliberations and analyses about what the many countries across the world and the United Nations could do in concert to behoove humankind.

Annual progress reports are produced each year and are available online at the United Nations Department of Economic and Social Affairs website that encompasses Sustainable Development.

All right, the keystone report was produced, countries are working on the direction and guidance provided, and there are yearly progress reports.

Time is ticking.

A line in the sand was identified as being fifteen years hence the original date of the pronouncement, thus the year 2030 is the point at which we will have preferably made all manner of tremendous progress on enacting the blueprint. Into this mix comes the further emerging grand convergence of advances in AI, along with the ubiquity of computing, and as I will cover momentarily, an infusion of AI systems into the SDG pursuits.

I don’t want to get ahead of myself on this. Let’s make sure that the SDGs are sufficiently placed on the table before we get to the AI infusion aspects.

The most commonly known or popularized aspects of The 2030 Agenda consist of seventeen distinct Sustainable Development Goals. Each SDG can be viewed somewhat on a standalone basis. We are to do what we can for each one of the seventeen. At the same time, it would be wisest to construe the seventeen SDGs as inextricably intertwined. The odds are that we can only make solid progress on any given one of the SDGs if we are also making progress on some or all of the others too.

There is the other side of that coin that comes to bear too. If we continue to do poorly on one of the SDGs or get worse on the matter, this is bound to drag down one or more of the other SDGs. The old saying that a rising tide raises all boats comes to mind in this circumstance. The SDGs will tend to rise or fall as a collection. That being said, we cannot give up on any particular SDG simply because we might realize that another SDG is not doing well. Individual SDG improvement is still possible and earnestly sought.

A shorthand title of each SDG is a handy way of quickly grasping what the SDGs consist of (this is from the official UN SDG document):

1. No Poverty

2. Zero Hunger

3. Good Health and Well-Being

4. Quality Education

5. Gender Equality

6. Clean Water and Sanitation

7. Affordable and Clean Energy

8. Decent Work and Economic Growth

9. Industry, Innovation, and Infrastructure

10. Reduced Inequalities

11. Sustainable Cities and Communities

12. Responsible Consumption and Production

13. Climate Action

14. Life Below Water

15. Life On Land

16. Peace, Justice, and Strong Institutions

17. Partnerships for the Goals

Just in case those shorthand versions don’t seem to convey to you the overarching nature of each SDG, I provide here a slightly more elaborated formal indication from the UN SDG report:

• Goal 1. End poverty in all its forms everywhere
• Goal 2. End hunger, achieve food security and improved nutrition, and promote sustainable agriculture
• Goal 3. Ensure healthy lives and promote well-being for all at all ages
• Goal 4. Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
• Goal 5. Achieve gender equality and empower all women and girls
• Goal 6. Ensure availability and sustainable management of water and sanitation for all
• Goal 7. Ensure access to affordable, reliable, sustainable and modern energy for all
• Goal 8. Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
• Goal 9. Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
• Goal 10. Reduce inequality within and among countries
• Goal 11. Make cities and human settlements inclusive, safe, resilient and sustainable
• Goal 12. Ensure sustainable consumption and production patterns
• Goal 13. Take urgent action to combat climate change and its impacts
• Goal 14. Conserve and sustainably use the oceans, seas and marine resources for sustainable development
• Goal 15. Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
• Goal 16. Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
• Goal 17. Strengthen the means of implementation and revitalize the global partnership for sustainable development

The SDGs are extensively detailed in the UN SDG reports and supporting documents.

Allow me to provide a few other insights as some additional considerations.

The numbering scheme does not denote priority or sequencing. Think of the numbering as merely a convenient form of reference when discussing the SDGs. Specialists for example that are concentrating on dealing with worldwide poverty are apt to at times refer to this SDG as simply Goal #1, but that doesn’t mean that it is the first or topmost goal per se. Those that are stridently working toward say peace and justice as part of Goal #16 are still to be seen as (shall we say) a topmost goal too. The reference number is nothing more than a reference number and does not imply or connote a lower or higher priority.

Another quick point is that you should refrain from doing the old toss the baby out with the bathwater if you have some qualms or disagreement with any particular SDG. In essence, some people might not necessarily agree with all of the seventeen SDGs. In that manner, they tend to discard all of the SDGs. That is short-minded. There might also be grumbling about whether a given SDG is able to be equated on par with each of the other seventeen. Again, do not misguidedly disregard all of the SDGs simply due to a personal perspective about one or another of the set.

The macro view is that these are all worthy of attention.

Put your attention toward the SDGs that you think you can most help out. If perchance you don’t favor some of the SDGs, so be it. Keep your focus then on the ones that you can support.

AI As A Catalyst For And Yet Also Against The SDGs

We are now ready to shift gears and discuss how AI comes to play for the SDGs.

I have elsewhere expounded in great detail about AI for each of the respective SDGs, see the link here. For space constraint purposes herein, I will provide a quick summary for you.

Remember too that we are going to first cover the positive use of AI, namely the AI For Good that contributes toward attaining the given SDG. I’d say this is the smiley face portrayal. We will afterward cover the frown face portrayal.

AI For Good that aids and emboldens each SDG:

1. No Poverty – AI that is used to combat poverty, spurs equal rights to economic resources and basic resources, accelerates investment in impoverished areas, and enables the advent of social protection systems

2. Zero Hunger – AI that increases dramatically agricultural production, aids especially small-food producers, is used for biosystem genetic diversity of seeds and cultivated plants and improves food commodity markets and trading practices

3. Good Health and Well-Being – AI that reduces neonatal morality and ends preventable deaths of newborns, is used for tracking epidemics and hastening health recovery, used for family planning, enables universal health coverage, and supports the development of vaccines and medicines

4. Quality Education – AI that provides education and/or vocational training that is more readily accessible and less costly worldwide, supporting of education for children and adults, supports teacher education, encompasses cultural diversity and global citizenship

5. Gender Equality – AI that seeks to end all forms of gender discrimination, aids in detecting and eliminating harmful practices and provides universal access to reproductive health information

6. Clean Water and Sanitation – AI that aids in testing to ensure that water is safe, reduces costs to make drinking water more affordable, integrates and enhances water resources management, and improves the protection and restoration of water-related ecosystems

7. Affordable and Clean Energy – AI that can be used to stoke affordable energy services, promotes and leverages the use of renewable energy, and facilitates clean energy research and the development of energy infrastructure

8. Decent Work and Economic Growth – AI that produces heightened levels of economic productivity, sparks employment diversity, supports entrepreneurship and decent job creation, protects labor rights, and promotes safe and secure working environments

9. Industry, Innovation, and Infrastructure – AI promotes inclusive and sustainable industrialization, enables developing countries to increase small-scale industrial enterprises, and enhances scientific research and technological capabilities in all countries

10. Reduced Inequalities – AI that progressively increases income growth, empowers inclusion of all, reduces inequalities, and facilitates responsible migration and mobility of people

11. Sustainable Cities and Communities – AI that seeks to provide affordable housing and basic services, improves transport systems, safeguards world cultural and natural heritage, and establishes stronger links among urban, peri-urban, and rural regions

12. Responsible Consumption and Production – AI that supports responsible consumption, especially in developing countries, reduces per capita global food waste, reduces waste generation, and provides the tools and information for lifestyles that can align in harmony with nature

13. Climate Action – AI that will enhance adaptive capacity for climate-related hazards and natural disasters, improves education and awareness-raising on climate, and assist in impact reduction and early warning notification

14. Life Below Water – AI that reduces marine pollution in all forms, is used to better manage marine and coastal ecosystems, assess scientific efforts to measure ocean acidification, and increase the transfer and sharing of marine technologies and knowledge

15. Life On Land – AI that aids in conservation and restoration of terrestrial ecosystems, supports retention of biodiversity, reduces degradation of natural habitats, detects impacts of invasive species, and assists in reducing or ending poaching

16. Peace, Justice, and Strong Institutions – AI will participate in reducing all forms of violence, detect and report on trafficking, reduce illicit financial and arms flows, alert on corruption and bribery, and strengthen efforts to combat terrorism and crime

17. Partnerships for the Goals – AI that makes global cooperation and collaboration on the SDGs a seamless and ready-made means of doing so, encourage multi-stakeholder partnerships and notably enhances data sharing, monitoring, and accountability associated with SDG realization efforts

My column coverage has touched upon many uses of AI that fit within the various SDGs. One, in particular, Goal #11 on the sustainability of cities and communities has been an especially notable focus. This has to do with my coverage and analysis of autonomous vehicles, such as self-driving cars, which are projected to eventually have an enormous impact on our day-to-day transportation, along with leading to significant changes in the design of our cities and how we live our lives. For a public policy study that I co-authored with Harvard, see the link here.

Now that we’ve covered the upside of AI infusion, you can take a breathtaking moment to bathe in the shiny glow that AI is indeed helping to realize the UN SDGs.

When you think you are ready for the AI ugly underbelly, continue reading.

I’ll wait.

Okay, first of all, AI can do the nearly opposite for each of the SDGs than what we want to have to happen. AI systems can be devised that intentionally undercut an SDG. This might be done for dastardly purposes. It could also be done under the belief by some AI developers or AI deployers that more money could be made by using AI adversely than it could when used positively (I realize this seems counter-intuitive, but it does happen, see my explanation at the link here).

AI For Bad can aim to achieve this (be forewarned this is a tough outlook to stomach):

1. Poverty – AI that increases global poverty

2. Hunger – AI that prolongs world hunger

3. Health – AI that heralds bad health and diminishes well-being

4. Education – AI that misinforms and devolves education

5. Gender – AI that worsens gender inequalities

6. Water – AI that boosts foul water and weakens waste sanitation

7. Energy – AI that makes energy costlier and less clean

8. Work – AI that saps decent work possibilities and stunts economic growth

9. Industry – AI that disrupts industries and raises vulnerabilities of the infrastructure

10. Inequalities – AI that sharpens and extends inequalities

11. Cities – AI that leads to less livable cities and communities

12. Food – AI that allows for irresponsible consumption and foul production

13. Climate – AI that delays and confounds climate action

14. Life Below Water – AI that harms life below the water

15. Life On Land – AI that harms life on land

16. People – AI that stokes violence and injustice

17. Partnerships – AI that makes partnerships for SDG arduous and undesirable

Yikes!

I warned you.

That list is quite distressing. For examples of some of the ways in which AI For Bad fits into the SDGs and how efforts are underway to combat or stifle AI For Bad, see my coverage at the link here.

Conclusion

Why have I let you in on the hiding-in-plain-sight secret that AI can be both positive and negative regarding the UN Sustainability Development Goals?

I do so for a pressing reason.

Much of the news coverage about AI for the UN SDG is picture-perfect. To some degree, this is welcomed. The idea is that the uplifting word is spreading that AI For Good is worthwhile. People that might not otherwise have considered using AI as part of the SDG’s aspiration are suddenly eye opened to the subject.

We cannot though let our guard down.

Either by purposeful evil-doing or by inadvertent oversight, the AI For Bad is and will continue to enter into the UN SDG pathway. Not being prepared for this is going to make things a lot worse. For each inch that we move forward on the SDGs, there is a mighty chance that the SDG progress will slide back two inches or more as a result of “caught by surprise” AI For Bad.

Do not fall into the easy dream that AI For Good is going to be the exclusive form of AI. AI For Bad is right on the heels, if not gaining added ground and getting into the lead. AI developers and all AI stakeholders need to be wary of AI that undercuts the UN SDGs. We need to try and prevent such AI or at least catch and defang such AI before it does damage that makes sustainability become a larger hole that needs to be filled rather than one that is already getting filled.

Let’s keep our attention riveted on all kinds of AI, encouraging AI For Good and fighting off AI For Bad.

Make that your AI sustainability goal.