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<title>Machine Learning and Society @ 🤗 </title>
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<h1>Machine Learning and Society @ 🤗</h1>
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<li><a href="index.html">ML&Soc Home</a></li>
<li><a href="projects.html">ML&Soc Projects</a></li>
<li><a href="topics.html">ML&Soc Topics</a></li>
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<aside>
<h2>Menu</h2>
<ul>
<li><a href="topics.html#Understanding">Understanding: Openness and the Science of AI</a></li>
<li><a href="topics.html#Developing">Developing: Openness, Business, and Competition</a></li>
<li><a href="topics.html#Deciding">Deciding: Openness, Transparency, Democratic Control over AI</a></li>
<li><a href="topics.html#Shaping">Shaping: Governing how AI Systems are Created, Shared, and Used</a></li>
<li><a href="topics.html#Systems">Safeguarding Systems: Impact of AI on Social Systems</a></li>
<li><a href="topics.html#Persons">Safeguarding Persons: Impact of AI on Individuals' Rights and Interests</a></li>
<li><a href="topics.html#Sustaining">Sustaining: Environmental Costs and Impact of AI</a></li>
<li><a href="topics.html#Discussing">Discussing: International Dynamics and Geopolitics</a></li>
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</aside>
<article>
<h2>Machine Learning & Society Topic Cards</h2>
<p>
The interaction between Machine Learning-based systems and their social context
can be examined through the lens of different inter-related topics. In our work,
we have found the following 8 topics to constitute a helpful way to organize resources:
</p>
<ul>
<li>
<a href="https://docs.google.com/document/d/102swvvpxj0K3nf0cNkmtIMg5CAD4yl_IO-ko75Uwc7Y/">
ML and Society Topic Cards Overview Document
</a>
</li>
</ul>
<section>
<h3 id="Understanding">Understanding: Openness and the Science of AI</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/1D2KA3CKcuKOc9mOMRKjucYrYBREx30z9xuKUGSgQUEE/">
Understanding: Openness and the Science of AI
</a>
</li>
</ul>
<p>
As AI is becoming ever more ubiquitous, increasingly more builders and affected
stakeholders need to understand how it works, what it can and cannot do, what trade-offs
are involved in developing the technology, and how it can be leveraged or improved in
particular contexts. This requires sufficient visibility and a thriving research ecosystem
that is inclusive of perspectives outside of those of the developers working within the
very best-resourced companies.
</p>
<p>
Making informed decisions about AI systems requires understanding how the technology works,
what development choices are available to meet certain goals, and how they trade off different
priorities. Approaching AI as a science means upholding scientific integrity, which includes
reproducibility, verifiability, and increasing the breadth of people who can use the technology
and contribute to scientific development.
</p>
</section>
<section>
<h3 id="Developing">Developing: Openness, Business, and Competition</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/17ksxEVyBcRGL6e6da4OPbjRxuCT5iEx5Ih67bj1Fc_w/">
Developing: Openness, Business, and Competition
</a>
</li>
</ul>
<p>
“AI” and Machine Learning systems are already ubiquitous, deployed in social
media and all kinds of digital services. AI can be compared to “Software 2.0” -
AI literacy is becoming part of the basic set of skills to build any kind of
technology. Relying exclusively on AI systems that are developed and served by a
handful of companies would have strong negative impacts on innovation and competition.
</p>
<p>
Having access to data is a significant competitive bottleneck, including: data about
how people are using AI systems - data about what AI systems are better or worse out -
use data and feedback from users - proprietary data to fine-tune models - internal databases
for RAG-like techniques. Sending all of that data to a few companies further centralizes
their role in adapting new technology. In addition to enabling anti-competitive practices,
this also limits the breadth of technology that can be developed - better to have smaller
companies work on their own hundreds of thousands of use cases than to have central entities
decide what is worth deploying and providing a “just OK” unique solution for everything.
</p>
</section>
<section>
<h3 id="Deciding">Deciding: Openness, Transparency, Democratic Control over AI</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/1PLNuZcal1z2tPbohhXEAoJAGr_GWbT0wkpulDtIJR6s/">
Deciding: Openness, Transparency, Democratic Control over AI
</a>
</li>
</ul>
</section>
<section>
<h3 id="Shaping">Shaping: Governing how AI Systems are Created, Shared, and Used</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/151vybUB-JMkMafAjXmw7pRcbbuWnJw3RtcAI4zsEcVk/">
Shaping: Governing how AI Systems are Created, Shared, and Used
</a>
</li>
</ul>
</section>
<section>
<h3 id="Systems">Safeguarding Systems: Impact of AI on Social Systems</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/1zhbaCZT8QDFHjhIlrnE-XObbXN8ZUMLhzrZYMFxBqFc/">
Safeguarding Systems: Impact of AI on Social Systems
</a>
</li>
</ul>
</section>
<section>
<h3 id="Persons">Safeguarding Persons: Impact of AI on Individuals' Rights and Interests</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/18DsFYeaoWcK8VOkl77E9AgdHA7vhyiqUhSmGm-vnIEE/">
Safeguarding Persons: Impact of AI on Individuals' Rights and Interests
</a>
</li>
</ul>
</section>
<section>
<h3 id="Sustaining">Sustaining: Environmental Costs and Impact of AI</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/1fgi2NEb4glP8QGansroHmL9BZJ6Ja8zQKWQY4STRQ3k/">
Sustaining: Environmental Costs and Impact of AI
</a>
</li>
</ul>
</section>
<section>
<h3 id="Discussing">Discussing: International Dynamics and Geopolitics</h3>
<ul>
<li>
<a href="https://docs.google.com/document/d/1BKXCx72vvdGAAzD6VGbPPBiA6AYdEHwDTwW07WBP084/">
Discussing: International Dynamics and Geopolitics
</a>
</li>
</ul>
</section>
</article>
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