Page 47 - AI for Good - Impact Report

AI for Good

Sustainable Development Goal 6: Clean Water

Ensure availability and sustainable management of
water and sanitation for all
SDG 6 currently has no targets on track, making it one of
the least progressing SDG goals. 228 This lack of progress
means that safe drinking water remains out of reach for
billions worldwide, with 2.2 billion lacking access to safely
drinkable water and 3.5 billion lacking access to safe sani-
tation. 229 With droughts becoming more common, this
situation is expected to worsen, endangering the lives of
billions of people. In 2022, roughly half of the world's popu-
lation experienced severe water scarcity for at least part of
the year, while one-quarter faced 'extremely high' levels of
water stress. 230

AI and SDG 6 Impact
According to a study on the impact of AI on
The connection between AI and SDG 6 is not extensively docu- SDG 6, AI could act as an (positive) enabler
mented in various AI UN use case repositories: 3 use cases out of f,or 100% of the targets and act as an inhibi-
40 in AI for Good: Innovate for Impact, 231 and approximately 50 use tor (negative) for 63% of the targets. (Nature
Communications, 2020)
cases out of 408 in the UN Activities on AI. 232 Specific use cases for Use case 1
water improvement can include data monitoring for water manage-
ment systems, which can optimize water flows to reduce energy and Implementing AI to monitor water
chemical usage while increasing water quantity. 233 This reduction consumption and to identify and address
overconsumption.
is crucial, as water and wastewater management organizations are
expected to invest around US$6.3 billion in AI solutions to enhance
their services. 234 Additionally, by improving climate event predic-
tions, AI can better help the system manage large water discharges,
which may occur more frequently due to increased flooding from
climate change. 235 AI solutions can also be used to locate new water
sources for at-risk communities or to test the water quality of those
sources. 236 Other use cases include AI-driven farming solutions that
reduce the need for irrigation, 237 asset monitoring in water systems link
to ensure ongoing maintenance, 238 monitoring the quality of lakes Use case 2
and other bodies of water, 239 and the use of AI to drive desalination Using AI in wastewater management
plant efforts. 240 systems to improve forecasting of the
system and reduce costs.
However, these solutions are often costly and may not be accessi-
ble to all countries or communities. 241 This is particularly critical as
water access issues affect regions differently, and most countries
affected by water issues are also the poorest, 242 making it even
more challenging for them to use AI solutions because AI itself
requires significant water usage to function. 243 From producing
the supporting hardware to the cooling of data centers, substantial
water quantities are needed, which could be polluted or inacces-
sible for individuals to meet their own needs. The numbers are link
quite significant, as it is stated that “the global AI demand may be Use case 3
accountable for between 4.2-6.6 billion cubic meters of water with-
drawal in 2027, which is more than the total annual water withdrawal Establishing AI use cases that can improve
of Denmark or half of the United Kingdom”. 244 flood and rain prediction to help the system
account for water changes.
Key Considerations for Stakeholders

• Impact assessment: The development of AI use cases and incentivess-
hould be aligned with OECD AI principles to maximise sustainable value
creation. 245 The objective is to prioritise governmental tools for AI use
cases related to the SDGs.
• Technology improvement: Reducing water consumption is imperative to
support the development of SDG 6 hence technologies with less water
use should be prioritized. 246 link

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