Why is community important in AI?
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Community is crucial in the field of AI for several reasons:
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Knowledge and Technology Dissemination: Building the capacity of local communities to understand and use technology effectively is essential. This includes strengthening tech-based education and enabling grassroots innovation. Empowering these communities allows them to decide how to integrate technology into their lives and fosters local innovation instead of relying solely on big tech companies 1.
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Continuous Data and Model Improvement: AI communities are vital for generating high-quality data needed for training models. As AI evolves, programming and software development continually introduce new packages and languages, requiring ongoing data updates. Without thriving communities, the data necessary to keep AI models relevant and efficient would dwindle 2.
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Resilience and Adaptation: Economic and community resilience is paramount for the successful adoption of technology. By having strong, knowledgeable communities, societies are better equipped to adapt and innovate in response to technological changes. This resilience is seen as a fundamental enabler for weathering transformative technological advancements 1.
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Accessibility and Inclusivity: The rapid advancement of AI is making it more accessible to casual users and non-experts. This democratization of AI helps lower barriers to entry, enabling more people and smaller entities to benefit from and contribute to AI developments. Open-source ecosystems are instrumental in this shift, breaking down proprietary barriers and promoting community-driven growth and innovation 3.
In summary, community involvement in AI is essential for fostering innovation, maintaining up-to-date data, ensuring resilience against technological shifts, and making AI accessible to a broader audience.
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