AI for Good: A Framework to Support Vulnerable People in Society
The potential for AI to help those who need it the most.
Lack of Digital Literacy and Accessibility: Vulnerable communities often face barriers in accessing and understanding AI technologies, hindering their ability to benefit from AI-driven solutions.
Insufficient Funding and Support for AI Initiatives: Departments and agencies that provide services to vulnerable communities often struggle with limited resources, making it difficult to invest in AI research, development, and maintenance.
Need for Meaningful Community Engagement: The success of AI initiatives in vulnerable communities hinges on active and meaningful engagement to ensure that the technology addresses their specific needs and concerns while avoiding cultural misunderstanding.
Our Advice
Critical Insight
To effectively leverage AI for the benefit of vulnerable communities, it is crucial for leaders to identify specific goals and needs, proactively engage with stakeholders and the targeted community, adopt an equity-centered implementation approach, and consider long-term sustainability and planning. The success of such initiatives hinges on the careful planning and execution of these steps.
Impact and Result
Foster Inclusive AI Ecosystems: Strive for inclusion by focusing on AI technologies that are specifically designed to serve the needs of vulnerable communities. This includes not only making tools user-friendly but also ensuring they are affordable and accessible.
Implement Ethical Oversight and Human-Centric Policies: Ethical oversight and human-centric design are vital for AI’s impact on healthcare, social services, and employment.
Establish Robust Privacy and Accountability Frameworks: Clear policies and trust-building measures, such as transparency and contestability, are needed for AI’s successful and value-aligned integration into social support.
Executive Summary
AI for Good: A Framework to Support Vulnerable People in Society
The potential for AI to help those who need it the most.
Analyst Perspective
Use the power of AI to unlock a new era of social empowerment.
Artificial intelligence (AI) has the transformative potential to both empower and challenge vulnerable communities. The onus is on federal governments to ensure that AI serves as an inclusive force, enhancing individual capabilities and transforming systemic structures in many sectors like healthcare, social services, and employment, which are widely used by vulnerable communities. Our research provides a dual-lens view, examining both the micro and macro impacts of AI, from enhancing personal functions to potential job displacement and ethical dilemmas that come with adopting computer systems.
Consider: while AI offers promising solutions for many areas, such as personalized healthcare and streamlined social services, it also poses challenges that require federal oversight, such as job losses, data privacy, and systemic biases. This report serves as a guide for federal action, offering actionable recommendations to ensure responsible AI deployment throughout departments and agencies that serve vulnerable communities. These include regulatory frameworks that address both individual and systemic challenges, as well as public-private partnerships to make AI accessible and beneficial for all.
Our aim is to equip federal policymakers with the insights and strategies needed to navigate the complexities of AI integration. By adopting a balanced approach that acknowledges both the challenges and opportunities presented by AI, federal governments can lead the way in creating a national AI ecosystem that is equitable, ethical, and truly beneficial for everyone, including the most vulnerable among us.
Paul Chernousov
Research Director
Industry Practice
Info-Tech Research Group
Executive Summary
Your Challenge
- Digital Inclusion: Federal governments need to make AI technologies available and accessible to vulnerable communities. The federal government plays a crucial role in promoting digital literacy for everyone.
- Resource Allocation: The financial and logistical burdens of implementing AI solutions can be overwhelming when aligning them to the needs of vulnerable communities. The federal government can support such communities by encouraging innovation and collaboration.
- Community-Centric AI: AI's effectiveness is measured by its acceptance and utility in the communities it aims to serve. This is not just a technological challenge but a social one, requiring active and meaningful community engagement.
Common Obstacles
- Lack of Digital Literacy and Accessibility: Vulnerable communities often face barriers in accessing and understanding AI technologies, hindering their ability to benefit from AI-driven solutions.
- Insufficient Funding and Support for AI Initiatives: Departments and agencies that provide services to vulnerable communities often struggle with limited resources, making it difficult to invest in AI research, development, and maintenance.
- Need for Meaningful Community Engagement: The success of AI initiatives in vulnerable communities hinges on active and meaningful engagement to ensure that the technology addresses their specific needs and concerns while avoiding cultural misunderstanding.
Info-Tech's Approach
- Foster Inclusive AI Ecosystems: Strive for inclusion by focusing on AI technologies that are specifically designed to serve the needs of vulnerable communities. This includes not only making tools user-friendly but also ensuring they are affordable and accessible.
- Implement Ethical Oversight and Human-Centric Policies: Ethical oversight and human-centric design are vital for AI's impact on healthcare, social services, and employment.
- Establish Robust Privacy and Accountability Frameworks: Clear policies and trust-building measures, such as transparency and contestability, are needed for AI's successful and value-aligned integration into social support.
Info-Tech Insight
To effectively leverage AI for the benefit of vulnerable communities, it is crucial for leaders to identify specific goals and needs, proactively engage with stakeholders and the targeted community, adopt an equity-centered implementation approach, and consider long-term sustainability and planning. The success of such initiatives hinges on the careful planning and execution of these steps.
What is artificial intelligence?
Definitions
- AI is human intelligence mimicked by machine algorithms. Examples: playing chess or Go.
- Machine learning (ML) is a subset of AI algorithms to parse data, learn from data, and then make a determination or prediction. Examples: spam detection, preventative maintenance.
- Deep learning (DL) is a subset of ML algorithms that leverage artificial neural networks to develop relationships among the data. Examples: image classification, facial recognition, generative AI (Gen AI).
What Makes AI Perform
- Algorithms
- Accelerators
- Big Data
What Makes AI Different?
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Unlock Sample ResearchContributors
- Dr. William Cowie, Executive Director, Every Canadian Counts Coalition
- Christine Trauttsmansdorff, Executive Director, Volunteer Ottawa
