Zeroing into the intersection of business, AI and social impact
- Padma Dayananda
- Dec 23, 2024
- 4 min read
In the third of a three part series, transformative social impact leader Padma Dayananda explains how artificial intelligence will help push forward the Social ESG agenda - and unlock opportunities for businesses.
Artificial Intelligence (AI) is the latest in a long line of technological disruptors that have revolutionized industries, from the mechanization of agriculture to the rise of the internet. Historically, such disruptions have brought with them uncertainties, job losses, and social imbalances, but their effects were often linear and confined to specific domains. AI is different.
As a self-learning, adaptive, and decision-making technology, AI’s impact is non-linear and spans across virtually every sector simultaneously. Its transformative potential promises unprecedented efficiencies and innovations, however it’s potential to deepen global inequities, reinforce historical biases, and perpetuate digital exclusion calls for businesses to adopt a nuanced and ethical approach to its development and deployment.
Positive Impacts: Democratization and Empowerment
Democratisation through open AI tools: Tools like ChatGPT, GitHub Copilot, and other open-access platforms are democratizing AI, enabling a wider range of users to benefit from its capabilities. These tools reduce barriers for small businesses and underserved communities, fostering innovation and economic participation.
Enhanced accessibility: AI-powered technologies like text-to-speech, voice recognition, and predictive typing empower individuals with disabilities, improving inclusion in education and the workplace. It can assist in identifying societal inequities by analyzing patterns in employment, education, or resource distribution. For example, it can uncover biases in hiring or disparities in access to essential services.
Precision in healthcare: Machine learning algorithms analyze medical data to detect diseases earlier, personalize treatments, and optimize hospital operations, significantly improving healthcare outcomes.
Sustainability and climate solutions: AI models optimize energy consumption, predict weather patterns for better agricultural planning, and reduce waste through smarter logistics.
Educational equity: AI’s ability to provide personalized learning and skill development empowers individuals, especially those in under-resourced or remote areas, creating pathways for greater social mobility.
Challenges: Cultural Bias and Inequities
Exclusion of 3.9 billion non-English speakers: Many AI models are developed in English speaking nations, reflecting a western perspective. This marginalizes billions of non-English speakers, limiting their access to AI-powered tools and creating a linguistic and cultural digital divide.
Historical bias in training data: AI systems learn from historical datasets that often carry inherent biases related to race, gender, and culture. These biases risk perpetuating inequities, embedding them into future technologies.
Cultural misappropriation and instability: AI systems designed with a western lens may inadvertently misrepresent or oversimplify cultural nuances, leading to misappropriation. When applied globally, such technologies can disrupt social harmony and exacerbate political instability.
Non-linear job displacement: Unlike past technologies, AI’s capacity for self-learning and adaptation enables it to displace jobs across diverse domains simultaneously, creating widespread economic and social disruption.
Role of businesses in building inclusive and ethical AI
Localizing AI development: Fostering and funding regional AI research and developing multi-lingual models ensuring that systems are designed with input from local experts can reduce cultural misrepresentation and linguistic exclusion.
Diversifying training data: Training datasets must reflect diverse languages, cultures, and demographics to prevent biases and promote inclusivity.
Collaborative governance: Governments, businesses, and civil society should collaborate to establish global standards for equitable and ethical AI use, addressing issues such as privacy, fairness, and cultural sensitivity.
Reskilling and workforce transition: Companies should proactively invest in reskilling programs to help employees and communities transition to new roles created by AI. This ensures that technological progress does not come at the cost of widespread unemployment
Investing in future talent: Businesses need to invest in providing future ready skills into educational institutions since the curriculum is already lagging and the AI spur will make the next generation workforce lacking in in-demand, relevant skills.
Inclusive Design: AI solutions should be designed with input from diverse stakeholders to ensure they serve a broad range of needs. Co-creating solutions with marginalized communities can help bridge gaps and foster inclusion.
Measuring Social Impact: Companies must track the social impact of their AI initiatives using clear metrics and report transparently on outcomes to ensure alignment with broader societal goals.
Conclusion
AI represents both an extraordinary opportunity and a profound challenge for humanity. Its transformative power lies in its ability to drive innovation and solve global challenges, but it also risks exacerbating inequities if not implemented responsibly. To navigate this duality, businesses must adopt a two-pronged approach: prioritize societal impact alongside AI-driven transformation.
This requires intentional design, collaboration, and a commitment to measuring and assessing the societal impacts of AI as an integral part of the transformation journey.
Through this balanced and inclusive approach, AI can transcend its risks and deliver on its promise to empower communities, drive economic growth, and create a more just and sustainable world.
With 23 years of cross-industry expertise, Padma is a transformative social impact leader specializing in digital transformation, business development, and ESG. She excels in leveraging business and technology to propel social sustainability initiatives and build impactful ESG programs, forging strategic partnerships across corporates, public sectors, and non-profits to facilitate major global deals.
As a skilled social value practitioner, Padma transforms CSR efforts into a competitive edge, helping businesses secure substantial public sector contracts. By seamlessly aligning social impact initiatives with overarching business objectives, she guides executive leadership in embedding sustainability into core strategies, achieving equitable outcomes and driving long-term growth. You can find Padma on LinkedIn here.