Page 43 - AI for Good - Impact Report

AI for Good

Sustainable Development Goal 3: Well-being

Ensure healthy lives and promote well-being for all at
all ages
SDG 3 is experiencing limited progress across all 13 targets,
with only 1 target on track (3.9 Health Impact of Pollution).
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The UN reports a global decline in life expectancy since
COVID-19, dropping from 73.1 years in 2019 to 71.4 in 2021.
Inequalities among regions significantly contribute to the
lack of access to health services and rising death rates,
posing challenges for lower- and middle-income countries
in achieving their targets. 183
AI and SDG 3 Impact
According to a study on the impact of AI on
AI’s impact on SDG 3 is well documented in various AI use cases reposito- SDG 3, AI could act as an (positive) enabler
ries: 20 use cases out of 40 in the AI for Good: Innovate for Impact, 184 and for 69% of the targets and act as an inhibitor
(negative) for 8% of the targets. (Nature
approximately 85 use cases out of 408 in the UN Activities on AI. 185 For Communications, 2020)
instance, AI can enhance diagnostics by efficiently reviewing patient data.
As stated in a recent article of the National Library of Medecine, “With the Use case 1
recent AI revolution, medical diagnostics could be improved to revolutionize Leveraging AI to improve and support
the field of medical diagnostics.” 186 This extends to the development of new patient diagnostics to help make the diag-
patient approaches, with practitioners increasingly seeking AI-driven tools nostic process faster, more efficient and
to enhance patient health and quality of life. 187 For example, new treatments transparent.
using AI to connect Amyotrophic lateral sclerosis (ALS) patients with their
loved ones were presented at the AI for Good Summit 2024. 188 Similarly,
robots are now providing comfort to patients and their families by taking
over some care activities. 189 Additionally, AI can support and expedite the
development of new drugs more efficiently, as demonstrated by the devel-
opment of one of the vaccines during the Covid_19. 190 AI can also optimize
the overall management of health-related processes, making them more
cost-effective. 191 By enhancing patient diagnosis and drug development, AI
has the potential to reduce the costs of medicine, making it more affordable.
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One significant risk associated with AI and SDG 3 is that many of these
use cases originate from developed countries, raising concerns about the Use case 2
affordability of these technologies for individuals in countries with fewer Using AI instruments to improve the qual-
resources. 192 This could widen the gap in SDG 3 outcomes between coun- ity of life of patients and their families by
tries. Additionally, mental health is increasingly negatively associated with generating new technology-driven solu-
AI, as practitioners are expected to keep up with new technologies, leading tions such as connected prosthetics.
to additional stress and feelings of inadequacy. 193 Governments should
account for this risk by putting the user at the center of AI development and
supporting patient-centric processes. Furthermore, health data is highly
sensitive, 195 and as AI relies on patient data, there is a significant risk of
creating biases based on discriminatory dimensions (gender, ethnicity, etc.)
or potential data breaches. These risks should be considered in the develop-
ment of solution. 196

Key Considerations for Stakeholders
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• WHO six AI principles: AI solutionsshould be aligned with the six
principles advocated by the WHO: 1) Protecting human autonomy, Use case 3
2) Promoting human well-being and safety and the public interest, 3) Implementing AI solutions at scale to drive
Ensuring transparency, explainability and intelligibility, 4) Fostering down the cost of medicine and related
responsibility and accountability, 5) Ensuring inclusiveness and equity, activities.
and 6) Promoting AI that is responsive and sustainable. 197

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