Harnessing AI for good: opportunities and challenges

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The AI for Good World Summit 2024 befell on Could 30-31 in Geneva, bringing collectively a bunch of over 2,500 members representing some 145 international locations. 

In her opening remarks, ITU Secretary-Basic Doreen Bogdan-Martin set the tone for the occasion by explaining the necessity for inclusivity in AI growth. 

She mentioned, “In 2024, one-third of humanity stays offline, excluded from the AI revolution, and with out a voice. This digital and technological divide is not acceptable.” 

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The summit showcased examples of AI functions, equivalent to Bioniks, a Pakistani-led initiative designing reasonably priced synthetic limbs, and Ultrasound AI, a US-based women-led effort enhancing prenatal care.

These contribute to an unlimited physique of tasks that really showcase how AI can speed up illness analysis, assist develop new medicine, present motion to those that misplaced it by way of damage illness, and way more. 

AI For Good additionally dived into how AI may also help attain the UN’s Sustainable Improvement Targets (SDG), which set out broad and far-reaching plans to develop and modernize less-developed nations whereas assuaging poverty, local weather change, and different macro issues. 

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Melike Yetken Krilla, head of worldwide organizations at Google, mentioned a number of tasks the place Google information and AI are getting used to trace progress towards the SDGs, map it across the globe, and collaborate with the World Meteorological Group (WMO) to create a flood hub for early warning methods.

AI can be serving to conservationists shield the setting, from the Amazon rainforest to Puffins off British coastlines and salmon in Nordic waterways

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AI’s potential for good – as per the Summit’s sentiment – is clearly substantial certainly.

However as ever, there may be one other half to the story. 

AI’s push and pull

Somewhat than one-way site visitors, AI tempts to each shatter and speed up digital divides.

For one, there may be robust proof that AI entrenches at present present divisions between extra and fewer technologically superior international locations. Research from MIT and the Knowledge Provenance Initiative discovered that almost all datasets used to coach AI fashions are closely Western-centric.

Languages and cultures from Asia, Africa, and South America stay primarily underrepresented in AI expertise, leading to fashions failing to precisely mirror or serve these areas.

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Furthermore, AI expertise is pricey and laborious to develop, and a choose few firms and establishments undoubtedly maintain nearly all of the management. 

Open-source AI tasks present a lifeline to firms globally to develop lower-cost, sovereign AI however nonetheless require computing energy and technical expertise that continues to be in excessive demand worldwide. 

AI mannequin bias

One other pressure on this push and pull is bias. When AI fashions are educated on biased information, they inherently undertake and amplify these biases. 

This may result in extreme penalties, notably in healthcare, schooling, and regulation enforcement. 

For example, healthcare AI methods educated predominantly on Western information might misread signs or behaviors in non-Western populations, resulting in misdiagnoses and ineffective therapies.

Researchers from main tech firms like Anthropic, Google, and DeepMind have acknowledged these limitations and are actively in search of options, equivalent to Anthropic’s “Constitutional AI.” 

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As Jack Clark, Anthropic’s coverage chief, defined: “We’re looking for a strategy to develop a structure that’s developed by a complete bunch of third events, moderately than by individuals who occur to work at a lab in San Francisco.” 

Labor exploitation

One other threat to harnessing AI for good is circumstances of labor exploitation for information labelers and annotators, whose process is to sift by way of hundreds of items of information and tag totally different options for AI fashions to study from.

The psychological toll on these employees is huge, particularly when tasked with labeling disturbing or express content material. This “ghost work” is essential for the functioning of AI methods however is continuously neglected in discussions about AI ethics and sustainability.

For instance, former content material moderators in Nairobi, Kenya, lodged petitions in opposition to Sama, a US-based information annotation providers firm contracted by OpenAI, alleging “exploitative circumstances” and extreme psychological well being points ensuing from their work.

There have been responses to those challenges, displaying how AI’s menace to weak populations can, with collective motion, be stamped out. 

For instance, tasks like Nanjala Nyabola’s Kiswahili Digital Rights Challenge goal to counteract digital hegemony by translating key digital rights phrases into Kiswahili, enhancing understanding amongst non-English talking communities in East Africa. 

Equally, Te Hiku Media, a Māori non-profit, collaborated with researchers to coach a speech recognition mannequin tailor-made for the Māori language, demonstrating the potential of grassroots efforts to make sure AI advantages everybody.

A balancing act

The push and pull of AI’s advantages and downsides can be difficult to stability within the forthcoming years. 

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Somewhat than representing a brand new paradigm of worldwide growth, AI is a continuation of a long time of discourse investigating the impacts of expertise on world societies. It’s each extremely common and extremely localized. 

Giant-scale AI instruments like ChatGPT can present a ‘blanket’ of encyclopedic data and abilities that billions can entry worldwide.

In the meantime, smaller-scale tasks like these described above present that, mixed with human ingenuity, we are able to construct AI expertise that serves native communities. 

Over time, the important thing hope is that AI will turn into concurrently cheaper and simpler to entry, empowering communities to make use of it as they like and, on their phrases, with their rights. In fact, that would additionally embody rejecting AI altogether. 

AI – each the generative fashions created by tech giants and conventional fashions created by universities and researchers – can actually supply societal advantages. 

There’s a lot to be skeptical and hopeful about. Such was the promise of different applied sciences earlier than AI, from the printing press to the combustion engine.

AI may prolong extra deeply into society than different applied sciences, but it surely stays beneath human management for now.

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