Industry Insights with AmitKumar Shrivastava

Artificial Intelligence & Machine Learning , Government , Industry Specific

How AI Is Shaping an Inclusive and Diverse Future

AI's Transformative Impact and Challenges in Developing Regions
How AI Is Shaping an Inclusive and Diverse Future

Artificial intelligence is steadily emerging as a driver in bridging the digital divide and fostering inclusivity, particularly in developing regions where disparities in health, education and economic opportunities are most acute. The widespread digitization across these regions is not just a technological revolution; it's a data revolution. This abundance of data is pivotal for AI, allowing it to address complex societal challenges in various sectors such as weather forecasting, healthcare and agriculture, thereby unlocking the potential for a more inclusive future.

See Also: When Every Identity is at Risk, Where Do You Begin?

AI in Weather Forecasting

One of the most significant examples of AI's impact is seen in India's adoption of AI in weather forecasting. This innovative shift from traditional methods to AI-enhanced models has revolutionized how weather-related information is processed and disseminated. By employing AI for high-resolution data collection at even the village level, India ensures that its diverse geographic and agricultural landscapes are better understood and catered to.

AI's application in meteorology extends to public alerts on heat waves and health advisories, such as those for malaria, ensuring that forecasts and warnings are precise, localized and relevant to the varied needs of the vast population. This approach improves the efficacy of weather-related information and democratizes its accessibility, playing a pivotal role in India's inclusive response to the complexities of climate change.

AI for Diversity and Inclusion

AI Mission

India's forthcoming AI Mission, announced by Prime Minister Narendra Modi, is a proactive step in harnessing AI to enhance diversity and inclusion. This initiative aims to unleash AI's capabilities in crucial sectors such as agriculture, healthcare and education, focusing on extending its benefits to Tier II and Tier III cities. The mission is pivotal in democratizing AI education and skill development through India's extensive network of Industrial Training Institutes. It emphasizes fostering ethical AI practices and developing transparent, unbiased systems to prevent societal disparities.

Strategic plans include a substantial increase in computing capacity, creating a Digital Public Infrastructure for startups and facilitating access to anonymized datasets, all aimed at cultivating an inclusive AI ecosystem. These steps highlight India's commitment to using AI for societal inclusivity and bridging technological divides.

Challenges for Developing Regions

Despite AI's potential to enhance diversity and inclusivity, its implementation in developing regions faces unique challenges. One is ensuring that AI systems are unbiased and representative of the diverse populations they serve, especially given the risk of perpetuating existing societal biases. Addressing the digital literacy gap is critical, as marginalized groups may lack the necessary skills to benefit fully from AI technologies.

The risk of exacerbating existing inequalities must be considered, as those with limited access to technology could be further marginalized. Developing inclusive AI solutions requires a concerted effort to understand and integrate these populations' diverse needs and contexts. In Telangana, a faulty algorithm initially intended for criminal profiling mistakenly denied thousands of people essential welfare benefits, including subsidized food. This misuse breaches rights under the Indian food security law and underscores the risks of unregulated AI in critical public welfare decisions.

In Uttar Pradesh, AI initiatives are enhancing diversity and inclusion. The state government's implementation of an AI-based common beneficiary database is streamlining the delivery of schemes, ensuring targeted assistance. AI bots in secondary schools are transforming education by monitoring examinations, assessing performance and identifying educational gaps. During the migrant crisis, an AI-powered portal facilitated crucial services such as direct benefit transfers, food distribution and job matching based on migrant skills. And integrating AI education in madrasas brings modern technological skills to these institutions, opening new employment opportunities and mainstreaming education for madrasa students.

LLMs to Enhance Communication and Diversity

Developing large language models for India's linguistic diversity highlights AI's role in promoting inclusivity. By addressing challenges such as diverse languages, dialects and the predominantly oral nature of many Indian languages, LLMs can transform sectors such as government, healthcare and education by improving services and altering job dynamics. Initiatives such as Bhashini and Bhasha Daan focus on enriching AI models with Indian languages and contexts, which is crucial for breaking down language barriers and fostering growth across India.

Tools such as LiveTalk are revolutionizing communication accessibility. This software, equipped with multilingual translation and real-time speech recognition, displays spoken words as text in various languages, aiding deaf individuals and facilitating cross-lingual interactions in international conferences and business meetings.

Generative AI advances inclusivity and diversity across multiple dimensions. Enhancing language and communication breaks down linguistic barriers, enabling access to information and services in many languages. In content creation, it reflects diverse cultural perspectives, supporting multicultural understanding. For individuals with disabilities, it offers accessible solutions through real-time translations and descriptions. Generative AI also devises innovative, tailored solutions for unique challenges marginalized communities face, demonstrating its potential as a tool for social good and equality.

AI in Public Health and Agriculture

In emergency management, AI-driven tools such as disaster maps revolutionize crisis response crisis responses. These tools enable efficient resource allocation and targeted emergency responses by accurately analyzing data, benefiting vulnerable communities.

AI has had an impact on public health, especially in developing countries. During the Ebola outbreak in Sierra Leone, a company in Africa developed a natural language processing platform that enabled locals to communicate their experiences, providing insights for more effective public health strategies.

Researchers in Rwanda have used anonymized metadata from cellphone networks to develop detailed maps of wealth distribution, guiding aid organizations in resource allocation.

In agriculture, AI compensates for resource scarcity. In Africa, AI augments the capacities of agricultural extension workers, boosting productivity.

In healthcare, AI-powered advancements in telemedicine and virtual training address the skills deficit in regions that have a shortage of medical professionals.

Ethical Deployment and the Future of AI

The deployment of AI must be guided by responsible and ethical practices. These include considerations of data protection, transparency and bias. AI systems must be designed to avoid perpetuating societal biases and be accessible to all. Diversity and inclusion in AI development must be balanced. Project teams and stakeholders must understand the criticality of these factors to identify, monitor and mitigate potential risks and challenges.

The homogeneity in AI's development community can unintentionally inject biases into AI systems. Addressing this imbalance is crucial, as there is a growing recognition of the need for diversity and inclusion as critical elements in AI development.

If steered responsibly, AI offers a pathway to a better world by bridging gaps in healthcare, education and economic opportunities across diverse regions.

Incorporating incentives for data owners when their data is used underlines a commitment to inclusivity in AI. This practice is particularly effective in developing regions, encouraging a broader spectrum of individuals and communities to contribute their unique data. Such participation is vital for creating AI systems that reflect and serve diverse populations. Through this approach, we ensure that the benefits of AI are not only widely distributed but also grounded in a wide variety of data sources.

In the global arena, AI harbors the potential for both "AI colonization" and the creation of a more equitable world. In AI colonization, dominant tech regions dictate AI norms, infrastructure and applications, potentially widening the digital divide. This risk is particularly pronounced if AI development overlooks diverse needs and contexts, leading to a one-size-fits-all approach that marginalizes less technologically advanced regions.

If steered responsibly, AI offers a pathway to a better world by bridging gaps in healthcare, education and economic opportunities across diverse regions. The key lies in global collaboration, ethical AI frameworks and diverse representation in AI development to harness AI's transformative power for inclusive and sustainable global progress.

Practical Examples of AI Implementation at Fujitsu

Fujitsu is committed to the ethical and responsible deployment of artificial intelligence. We prioritize transparency, ethical development and accountable deployment practices, as demonstrated by our pivotal involvement in AI4People, an initiative to advance AI ethics and establish our AI Ethics and Governance Office. This office symbolizes our dedication to developing secure, safe and ethically aligned AI applications, and it steers our initiatives to meet the highest standards of ethics.

We introduced the AI Ethics Impact Assessment tool to embody our commitment to ethical AI use and build trust in its applications. This tool scrutinizes the ethical impacts of AI technologies on individuals and society before their deployment and is a critical instrument for designing and auditing trustworthy AI systems. It is included in the OECD.AI's Trusted AI Tool Catalog.

We have also developed technologies such as Wide Learning and Deep Tensor, which aim to enhance AI explainability and transparency and foster trust among our customers. We strictly comply with local AI development and deployment regulations and provide detailed, explainable AI reports when necessary.

Our digital twin linkage technology, the Actlyzer, uses AI to enhance workplace safety and efficiency through the 3D analysis of human behavior without retaining personal information. This underscores our firm stance on data privacy and security, with applications spanning various industries - including manufacturing and retail - and showcases our dedication to merging innovation with ethical responsibility.

Fujitsu actively promotes the responsible advancement and application of AI through these initiatives and technologies, ensuring that our solutions are beneficial, ethical and congruent with societal values. Our team of AI engineers is committed to projects related to AI ethics, and our AI professionals actively contribute to the discourse on AI ethics. They are sharing their expertise through writings and presentations, both internally and externally, to further the cause of responsible AI.

AI presents enormous opportunities for reducing inequalities and promoting inclusivity in developing regions, but its deployment must be guided by ethical practices and a conscious effort to integrate diversity and inclusion at every stage. By addressing these challenges head-on and leveraging AI responsibly, we ensure that the benefits of this revolutionary technology are shared by all, creating a more inclusive and equitable global society.

About the Author

AmitKumar Shrivastava

Shrivastava is the head of AI in Global Delivery Center India at Fujitsu. He has over a decade of experience in projects for AI, ranging from predictive analytics to cutting-edge deep learning technology. He is a Global Fujitsu Distinguished Engineer and a Fujitsu Fellow.

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