AI, Data and Humanity: Walking the Policy Plank
Saumya Anand – Student, Kautilya
Artificial intelligence (AI) is revolutionizing how we work and live while presenting many unimaginable opportunities. Data, the lifeblood of machine learning algorithms, is at the center of this AI revolution. “AI is the confluence of three components that came together to fuel the revolution: a new algorithm known as deep learning, GPU processors, and big data. The third element of the revolution, big data, is arguably the most important because it holds the most value”. These developments have raised profound questions about the future of work, the role of humans in an AI-driven world, and whether AI will ultimately replace humans in various aspects of life. The ethical and appropriate use of AI data is becoming a top priority for authorities everywhere. It’s like walking a tightrope to strike the correct balance between using AI’s capabilities for good and preserving privacy and human rights.
This blog will discuss the complex policy issues surrounding AI data and its effects on humanity.
The Privacy Paradox
AI needs a lot of data to develop its algorithms and make wise choices. Numerous sources, including private devices, social media, and public records, can be used to gather this information. However, serious privacy problems are raised by gathering and utilizing enormous volumes of data. Personal information is now being gathered, analyzed, and exploited by both governments and commercial entities in the digital age. A wake-up call was provided by the 2018 Cambridge Analytica scandal, in which the personal information of 50 million Facebook users was used for political objectives.
Many nations have implemented data protection legislation in response to growing privacy concerns. One such example is the EU’s General Data Protection Regulation (GDPR). It gives people more control over their personal data by forcing businesses to acquire explicit consent before collecting it. Explicit consent is one option for legitimizing the use of special category data. Consent can also legitimize restricted processing, and explicit consent can legitimize automated decision-making (including profiling), or overseas transfers by private-sector organizations in the absence of adequate safeguards. Similarly, India recently passed the Data Protection Bill, which recognizes the rights of all citizens to protect their data.
However, stricter data laws can stifle AI advancement by making getting the data needed to train algorithms more challenging. Governments must carefully navigate a policy tightrope to strike the correct balance between privacy and innovation.
Beyond Binaries: Unmasking Gender Bias in AI
Bias and fairness are two important challenges with AI data. AI systems may unintentionally reinforce and magnify pre-existing biases found in the data they are trained on. An AI program might, for instance, discriminate against ethnic or gender groups in lending or employment decisions if it was trained on biased historical data. “Studies on the use of AI has discovered gender bias in the outcomes of algorithm application, from natural language processing techniques which perpetuate gender stereotypes to facial recognition software which is much more accurate on male faces than female ones”. Gender disparities in the tech industry are well documented, with women and non-binary individuals underrepresented in STEM fields. As of 2023, women account for 27% of India’s STEM (Science, Technology, Engineering, and Mathematics) workforce, in contrast to 32% of the non-STEM labor force, according to the World Economic Forum’s recent Global Gender Gap Report 2023. This lack of gender diversity often leads to biased algorithms and discriminatory outcomes. For instance, the AI system may struggle to accommodate the needs and challenges faced by women and gender-diverse individuals if the dataset primarily consists of historical male perspectives.
To solve this problem, authorities must create standards and rules that guarantee AI systems are impartial and free from bias. This involves examining both the algorithms and the data used to train AI systems. A challenging and developing area of policy development is the auditing of AI algorithms for prohibiting discrimination and biases and the provision of principles for fairness in AI decision-making. Policymakers and technologists must work together to bridge this gap by ensuring that AI and data-driven innovations contribute to a more inclusive and equitable world.
National Security and Data Access: Juggling Priorities
Beyond issues with fairness and privacy, national security is a key factor in developing AI data policies. Governments worldwide are becoming increasingly interested in using AI for intelligence, espionage, defence and for cyberwarfare gaining strategic advantage. “In the golden era of digital development, legislators, law enforcement, and policymakers are facing a new challenge: respecting privacy while ensuring security; they now juggle with a need for privacy of data and their responsibility as state protectors, attempting to arrive at a method that ensures both”.
There is a clear conflict between individual rights and national security. It might be difficult to strike a compromise between the two. To establish accountability and supervision in these areas, policymakers must consider when and how governments might use AI data for security purposes.
AI Mosaic: The Interconnected Web
AI data is borderless. The internet allows for frictionless data transfer. The fact that AI data is worldwide poses particular difficulties for authorities. A patchwork of national laws might confuse and impede the advancement of AI technologies that are beneficial to all of humanity. Global governance with equal participation of all member states is necessary to make resources readily available, make representation and oversight mechanisms broadly inclusive, ensure accountability for adverse effects, and ensure that geopolitical competition does not drive reckless AI or hinder responsible governance.
International collaboration and standardization efforts are essential for overcoming these obstacles. Countries like Italy, Australia, and many others have raised this issue and come up with certain regulations. To develop global norms and standards, organizations like the United Nation and the World Economic Forum have started debates on AI governance and data sharing.
The technological revolution that is changing our world is centered on AI data. However, concerns are related to the responsible and ethical use of AI data. While the thin-ice walk between safeguarding human values and exploiting AI’s potential is quite a delicate task for policymakers, this journey’s navigation should be through innovation and courage.
*The Kautilya School of Public Policy (KSPP) takes no institutional positions. The views and opinions expressed in this article are solely those of the author(s) and do not reflect the views or positions of KSPP.