Introduction
The rise of Artificial Intelligence (AI) has become transformative for industries, boosting productivity and improving complex societal challenges. But for emerging markets—economies and infrastructures developing at a rapid rate—full adoption of AI has not progressed across the trust gap. Misgivings about AI derive from various reasons, such as data privacy, lack of regulation, cultural disbelief and inequalities in technology.
Closing the gap not only is a strategic need, but an enormous opportunity. This article will discuss why trust is key to the AI ecosystem, what the unique implications for emerging markets are, and what some inexpensive and scalable ways this can be done.
Understanding the AI Trust Gap
The AI Trust Gap is the gap between the potential of AI technologies and the public’s willingness to use the technology. The gap is even wider in emerging markets that have little digital literacy, ambiguous policies, and fear misuse of both the data and AI bias.
As an example, a Why rebuilding trust is key for the Intelligent Age of AI | World Economic Forum sought to understand how to build trust in AI and found that people in low-income countries are less likely to trust AI because of modelling on fear of surveillance, job loss and transparency in decision making.
The Need for Emerging Markets to Close the Trust Gap
1.Accelerated Development Potential
AI can dramatically transform many key sectors such as agriculture, health care, education, and financial inclusion in developing countries. For instance, AI-based platforms such as mPharma, are trying to address health supply chain challenges in Africa and make essential medicines more accessible.
2.Inclusiveness and Equality
If emerging markets do not embrace trustworthy AI, they will risk falling behind in the global digital economy. Closing the trust gap allows for inclusive access to AI innovations which increases opportunities for economic and social participation.
3.Competitive advantage
Emerging markets which develop local AI ecosystems with built-in trust mechanisms will welcome investment, talent and partnerships at the global level, outperforming other markets in the 21st-century economy.
Key Barriers to AI Trust in Emerging Markets
1.Data Privacy and Security
Weak data protection laws and scant exposure raise questions of how personal data is collected, stored, and used. For example, many African countries are still harmonizing with regulations somewhat like the General Data Protection Regulation (GDPR) – Legal Text, the European standard for data privacy.
2.Limited Regulatory Framework
In many emergent markets, the regulation of AI is nonexistent or only in the initial stages. When legal framework is missing, this means businesses and citizens will suffer from no guidance or protection which reinforces distrust.
3.Digital Literacy Gap
Many people still do not have basic digital skills which impedes the adoption of AI and increases vulnerability to misinformation, algorithmic bias, and exploitation.
4.Infrastructure issues
AI systems require robust data infrastructure, internet connectivity, and computational power. In many places, it remains an uphill battle to advance adoption in places where basic internet connectivity is lacking.
Proven Approaches to Close the AI Trust Gap
1.Transparent Governance and Regulation
Governance of AI should be top priority. Emerging market governments should:
Draft inclusive and clear policies regarding AI.
Draft a national AI strategy which includes consultation of all stakeholders.
Advocate for regulatory sandboxes as spaces for testing AI models with safety.
One successful example is Rwanda’s National AI Policy which lays out principles of ethics, principles of implementation and investment.
2.Invest in Digital and AI Literacy
Educating both citizens and policymakers is key to maximizing the benefits of AI. Governments and NGOs can:
Integrate AI, and its digital ethics to national curricula of education.
Support vocation training programs related to AI and data science.
Launch public-facing campaigns to remove the cloud of mystique around AI technology.
Organizations such asData Science Nigeria | Africa’s Foremost AI Organisation are already building AI capacity at the grassroots level with bootcamps, etc.
3.Build Local AI Ecosystems
Reliance on an imported AI systems can create issues of bias and accountability. Promoting local talent and intrapreneurship helps ensure cultural confidence and relevance. Governments can:
Invest public resources in local AI startups.
Develop innovation hubs and incubation programs for AI.
Establish public-private partnerships for AI Research and Development.
For example, Zindi is an African data science competition platform that unlocks local talent to improve lives with AI technology in communities.
4.Practice Data Inclusiveness
Trustworthy AI technology relies on ethical, high-quality, and representable data. To practice data inclusiveness:
Implement data sovereignty policies for the questionnaire-based datasets and local data sovereignty.
Teach data collection methodology that emphasizes ethics in data collection.
Promote frameworks for open data and available shared data collection for innovation.
Initiatives such as the Open Data for Development (OD4D) project is working across countries and regions to improve access and responsible data use.
5.Promote Ethical AI Standards
Ethics is essential; therefore, there can be no trust. Emerging markets should establish ethical frameworks for AI behavior and use, including:
- Fairness and non-discrimination.
- Transparency and explainability.
- Accountability and means of redress.
The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems has curated resources in support of responsible governance of the ethical implementation of these ethical frameworks.
6.Community Engagement and Co-Creation
AI outcomes cannot be imposed, they must be co-created with communities. Engaging community members upfront and throughout the AI design/deployment process helps AI developers understand local concerns and foster trust, including, for example:
Consultative community engagement.
Integrating local/regional Indigenous knowledge into algorithms.
Designing user-focused, user-friendly interfaces in regional languages.
The AI4D Africa initiative is focused on empowering European, American, African and Asian voices in the design of AI policies and solutions.
Role of International Cooperation
Emerging markets cannot close the trust gap alone. There must be international cooperation to share best practices, technologies, and funding. The Artificial Intelligence – AI | UNESCO and World Bank are already supporting responsible implementation of AI around the globe.
Sharing technology agreements, bilateral agreements on AI and international research exchanges for AI firm will create the momentum needed for sharing best practices of responsible ethical AI.
Case Study: Responsible AI for Social Empowerment (RAISE) in India
India’s RAISE 2020 initiative is a prime example of how a large population of an emerging market can scale AI and build trust through ethical, inclusive, and public-private partnerships. Through RAISE, India demonstrated through transparency and governance how AI can reduce inequalities and be utilized for the benefit of the many, and not just the few.
Measuring trust: An AI Trust Index
An AI Trust Index can be developed that measures AI implementation at different AI actions across trust variables such as privacy, fairness, accessible and user trust. An AI Trust Index will allow emerging markets to measure progress and benchmark against themselves. If properly defined, an AI Trust Index will allow for the ability to re-evaluate policy change and develop better fit-for-purpose AI policies.
Conclusion: A Call to Action
Bridging the AI trust gap for communities in emerging markets is urgent and can be done. The future trajectory of AI in emerging markets will not be determined solely by the availability of new AI technology, rather it will be determined by the public’s perception of fairness, transparency, and purpose. Supportive, ethical, inclusive governance, thoughtful design, community engagement and international support can assist emerging markets to develop a future based upon AI to genuinely benefit the many, rather than the few.
As governments, private sector enterprises, civil society and the academic community begin the collaborative process of empowering developing markets, collaboration becomes normal, rather than the exception.
