In the AI race, investor-led standards and investment strategies will play a role in ethics and wealth creation in the developing world.
Over the last year, I’ve been part of the Lord Mayor’s Ethical AI Initiative in the City of London.
This engagement has enabled successful AI Ethics training and certification for over 6,000 people in 50 countries. Additionally, our work encouraged institutional investors with over $30 trillion of Assets Under Management to pledge support for ethical AI standards around bias, transparency, accountability, and safety, and the use of the existing ISO 42001, which seeks to ensure responsible development and use of AI systems, rather than creating new, competing standards. ‘
We also established a permanent Investor Council on Responsible AI, or ICRAI. These achievements show the power of investor-led standards and the role that leading global financial centres can play in their facilitation.
One of the things we are trying to unravel is how we, the investor community, can be more proactive in setting and enforcing standards that ensure emerging technologies are creating global economic opportunities without compromising ethical considerations. This investor-led push is not designed to replace regulation, far from it.
Regulations are emerging, from the EU AI Act 2024 that takes a more protectionist view of individual rights, to the US which may lean towards a more innovation-fostering free market approach with the incoming Trump administration. Investor-led standards can form consistent ground rules protecting against systemic risks AI may pose to the financial system, and the potential misuse by companies deploying AI that receive funding through equity or debt.
This is especially important in developing economies, where regulations are sometimes absent or haven’t evolved compared to their developed country counterparts. As an emerging market fund manager, I have seen the positive effects of upholding investor-led standards, for example in corporate governance and Environmental and Social Governance, that are often more stringent than local laws and regulations.
I have also experienced the benefits of focusing an investment strategy on such markets, something the global venture capital industry could learn from.
Protecting ‘algorithm takers’
I use the term Algorithm Takers to describe those, such as gig economy workers, who live at the mercy of algorithmic decisions. This includes not only delivery riders, but also end users of health care, criminal justice, or government services that deploy AI to make life-changing decisions, sometimes for the most marginalised in society. “Code Dependent,” a book by the Financial Times AI editor Madhumita Murgia, highlights stories of AI-induced human rights issues, and not just in the developing world. In addition to healthcare in India, and social services in South American slums, she covers Amsterdam’s AI-assisted predictive policing which disproportionately affected certain immigrant communities.
Another example is the AI data labeling market, employing millions around the world to create training data sets. We have invested in one such company that employs 8,000 people across Nepal and Kenya. We found that our investor-driven labor standards empowered the company’s workforce model of distributed teams to earn an average of three times the minimum wage. The work provides experience working in an international project management setting. However, on the flip side, some companies in this market have allegedly exploited workers in developing countries.
Empowering algorithm makers
Much of the attention is on algorithms and AI activity in the developed world. What is less often covered is that AI software is increasingly written in the developing world.
The digital revolution — the confluence of machine learning, cloud computing, and processing power — along with post-COVID workforce models, renders the geographic location of the Algorithm Makers, and the startups they work for, less relevant. The jobs and economic returns from previous industrial revolutions were geographically tied to physical infrastructure – e.g. mills, factories, transportation. But those countries without the infrastructure — that is, most of the world — were left behind in the economic race.
This led to a surge in productivity and growth in developed nations, but huge wealth and income inequalities with developing nations. In recent decades, infrastructure and policy have seen China, Asian “tiger’ economies and, more belatedly, India rapidly catch up, while Least Developed Countries, with 880 million people, or 12% of the world’s population, were left behind.
The digital revolution holds a more egalitarian promise – countries don’t need advanced physical infrastructure to participate, just brains and broadband. The demand for the digital workforce is ballooning, especially for AI engineers and data scientists.
Another of our portfolio companies makes AI Engines for global enterprise clients, with use cases including fraud detection, GenAI data extraction from handwritten datasets, and GenAI answer generation from corporate documents. While the sales office is in the US, the software is written not in California, but Kathmandu, and implemented by hundreds of highly trained AI engineers in Nepal. Recognising there is an education deficit between Nepal and the software’s target markets, the company upskills Nepali engineers to global standards before they begin. Despite the cost of training, the company delivers its products and services at a cost advantage.
Big tech companies like Microsoft are also investing in training and job creation in the ASEAN region. Similarly, government bodies from developed economies are enabling data and AI-led opportunities in underserved markets. For example, the German Federal Ministry for Economic Cooperation and Development collaborates with local partners in countries like Rwanda, Uganda, and Kenya to develop open AI training datasets in local languages, thus furthering demand for related skills in these markets.
Collectively, these efforts represent a historic opportunity to open the economic benefits of the digital and AI revolution to developing economies. Or, to empower them to become Algorithm Markers, not just Takers.
This won’t happen on its own. The global (and mostly US) venture capital industry must actively increase their pipeline beyond Silicon Valley and other well-trodden tech hubs. It was the original industrial revolution that first created economic inequality between the West and the rest. Could the digital revolution in part rebalance such inequality?
Balancing innovation and social responsibility
Despite their untapped potential, developing markets, more specifically LDCs, receive a tiny portion of global investment flows from private equity and venture capital firms – LDCs account for less than one percent of world trade and foreign investments, despite these countries being home to 12 percent of the world’s population. Today, most venture capital investments are still concentrated in the US, UK, and China.
Private capital, including venture capitalists, asserts substantial influence over how technology evolves. In 2023 alone, close to $315 billion was invested in tech companies globally. VCs and other impact investors are often known to spearhead the ground rules that protect workers, inform ethical decision-making, and ensure fair treatment of all constituencies within the ecosystem of tech innovation.
With developing countries set to experience more job growth in the tech-driven economy – both through the gig economy and as software developers themselves – investors must be open to shouldering responsibility of industry standardization and ethical oversight.
Simultaneously, investors must prioritise standards that ensure adequate employee and user protection, while avoiding “data colonialism” and the stifling of innovation. By setting clear, ethical standards and collaborating with local governments to support sustainable practices, technology-enabled job growth could lift millions out of the endless cycles of socio-economic distress and exploitation. Similarly, these markets could benefit from localised applications of technology innovation.
Through this proactive and intentional approach, investors who are willing to champion ethical and sustainable technology use, will help maximise the true potential of AI and other digital technologies. Ultimately, it comes down to investors’ ability to approach these standards not as constraints, but as enablers of sustainable growth.
To truly harness the power of AI and other digital technologies, investors must be willing to weave social equity into their ambition of financial returns. Only then can we foster a balanced, ethical and inclusive global technology ecosystem.
Tim Gocher OBE is the CEO and Founder of Dolma Fund Management.
