- Prelims: Science and technology, Artificial intelligence(AI), Generative AI, Big Data, GANs, ChatGPT1 tool, DALL.E2 etc
- Mains GS Paper III and IV: Significance of technology for India, AI, indigenisation of technology and development of new technology.
ARTICLE HIGHLIGHTS
- AI is projected to add $500 billion to India’s economy by 2025, accounting for 10% of the country’s target GDP.
INSIGHTS ON THE ISSUE
Context
Artificial intelligence(AI):
- It is a branch of computer science dealing with the simulation of intelligent behavior in computers.
- It describes the action of machines accomplishing tasks that have historically required human intelligence.
- It includes technologies like machine learning, pattern recognition, big data, neural networks, self algorithms etc.
- g: Facebook’s facial recognition software which identifies faces in the photos we post, the voice recognition software that translates commands we give to Alexa, etc are some of the examples of AI already around us.
Generative AI:
- It is a cutting-edge technological advancement that utilizes machine learning and artificial intelligence to create new forms of media, such as text, audio, video, and animation.
- With the advent of advanced machine learning capabilities: It is possible to generate new and creative short and long-form content, synthetic media, and even deep fakes with simple text, also known as prompts.
AI innovations:
- GANs (Generative Adversarial Networks)
- LLMs (Large Language Models)
- GPT (Generative Pre-trained Transformers)
- Image Generation to experiment
- Create commercial offerings like DALL-E for image generation
- ChatGPT for text generation.
- It can write blogs, computer code, and marketing copies and even generate results for search queries.
Investments in AI:
- Microsoft decided to invest $10 billion in the OpenAI project
- Google introduced its chatbot, Bard.
- World’s leading GPU manufacturer NVIDIA reached a market cap of a trillion dollars.
- Amazon introduced Bedrock, giving its customers access to large language models of its own called Titan.
- Google uses generative models to improve its search engine and
- Microsoft integrates generative models for Windows 11 navigation.
Recent Issues found around the AI:
- There are real dangers of LLMs in particular, and of publicly deployed AI systems in general.
- AGI is imminent and could prove to be an existential threat.
- Data hunger of AI which has implications on both diluting privacy and on labor conditions of platform workers.
- AI’s stochastic and opaque workings which have impacts on democratic processes
- when AI systems are used in public-use cases like surveillance and policing
- Propensity of AI systems in replicating and strengthening structural problems.
The practical consequence of AI:
- AI is too complex to regulate or even be understood by governments.
Global regulations:
USA’s executive order on AI:
- The US government had persuaded the companies OpenAI, Microsoft, Amazon, Anthropic, Google, Meta, etc to abide by “voluntary rules” to “ensure their products are safe”.
- The US administration signed an “Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence”.
Europe’s AI Act:
- Unlike the US executive order, the EU law has concrete red lines
- It has prohibited arbitrary and real-time remote biometric identification in public spaces for law enforcement.
- It bans emotion detection, which is now recognised to be a harmful pseudoscience, in workplaces.
- It prohibits authorities from using AI systems to generate social scores/credits.
Issues with the Law:
- Emotion detection is outside the regulatory ambit as long as it’s not used in workplaces
- It leaves scope for the use of this harmful and fraudulent tech.
- The law doesn’t address virtual assistants and chatbots with the potential for damage (one common and harmful example is apps using chatbots to give physical and mental health advice).
- There is still a complete lack of industrial policy anywhere on AI,
- Vague frameworks of “trust” and “responsible AI” fill this vacuum.
Challenges:
- Aligning AI with universally accepted human values.
- The rapid pace of AI advancement, spurred by market pressures, often eclipses safety considerations, raising concerns about unchecked AI development.
- Governance: lack of a unified global approach to AI regulation can be detrimental to the foundational objective of AI governance — to ensure the long-term safety and ethical deployment of AI technologies.
- The AI Index from Stanford University reveals that legislative bodies in 127 countries passed 37 laws that included the words “artificial intelligence”.
- There is a conspicuous absence of collaboration and cohesive action at the international level, and so long-term risks associated with AI cannot be mitigated.
- If a country such as China does not enact regulations on AI while others do, it would likely gain a competitive edge in terms of AI advancements and deployments.
- Unregulated progress can lead to the development of AI systems that may be misaligned with global ethical standards, creating a risk of unforeseen and potentially irreversible consequences.
- It could result in destabilization and conflict, undermining international peace and security.
- Nations engaging in rigorous AI safety protocols may be at a disadvantage
- Encouraging a race to the bottom where safety and ethical considerations are neglected in favor of rapid development and deployment.
- The uneven playing field can inadvertently encourage other nations to loosen their regulatory frameworks to maintain competitiveness, thereby further compromising global AI safety.
Ethical Issues with AI:
Way Forward
- The confluence of technology with warfare amplifies long-term risks.
- Addressing the perils of military AI is crucial.
- The international community has formed treaties such as the Treaty on the Non-Proliferation of Nuclear Weapons to manage such potent technologies
- Demonstrating that establishing global norms for AI in warfare is a pressing but attainable goal.
- There are significant challenges to AI policy, but a dearth of democratic voices and the tendency to surrender the policy process around AI to a handful of tech companies need to be extended.
- India can assume leadership in how regulators address children and adolescents who are a critical demographic in this context.
- Regulation should avoid prescriptions and instead embrace standards, strong institutions, and best practices which imbue openness, trust, and accountability.
QUESTION FOR PRACTICE
What are the different elements of cyber security ? Keeping in view the challenges in cyber security, examine the extent to which India has successfully developed a comprehensive National Cyber Security Strategy.(UPSC 2022) (200 WORDS, 10 MARKS)
