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EDITORIAL ANALYSIS : Reflections on Artificial Intelligence, as friend or foe


Source: The Hindu

  • 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.


  • The Association for Computing Machinery released a statement on ‘Principles for Responsible Algorithmic Systems’, a broader class of systems that include AI systems.
  • There have been different cautionary messages about AI, issued by the Future of Life Institute, the Association for the Advancement of Artificial Intelligence and the Center for AI Safety.




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.


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.


Areas of use, limitations and AGI:

  • AI systems are capable of exhibiting superhuman performance on specific or “narrow” tasks.
    • Example: In chess, Go (a game several orders harder than chess)
    • In biochemistry for protein folding.
  • The performance and utility of AI systems improve as the task is narrowed, making them valuable assistants to humans.
  • Speech recognition, translation, and even identifying common objects such as photographs, are just a few tasks that AI systems tackle, even exceeding human performance in some instances.



  • Their performance and utility degrade on more “general” or ill-defined tasks.
  • They are weak in integrating inferences across situations based on the common sense humans have.
  • Artificial General Intelligence (AGI)
    • It refers to intelligence that is not limited or narrow.
    • There are no credible efforts towards building AGI yet.
  • Common sense will make a human save his life in a life-threatening situation while a robot may remain unmoved.


Release of ChatGPT:

  • It is a generative AI tool that uses a Large Language Model (LLM) to generate text.
  • LLMs are large artificial neural networks that ingest large amounts of digital text to build a statistical “model”.
  • Several LLMs have been built by Google, Meta, Amazon, and others.
  • ChatGPT is generating flawless paragraphs that caught the world’s attention.
    • Writing could now be outsourced to it.
  • sparks of AGI” in GPT-4; AGI could emerge from a bigger LLM in the near future.


Limitations of LLM:

  • At the basic level, LLMs merely predict the most probable or relevant word to follow a given sequence of words, based on the learned statistical model.
  • They are just “stochastic parrots,” with no sense of meaning.
  • They “hallucinate” facts, confidently (and wrongly) — awarding Nobel prizes generously and conjuring credible citations to non-existent academic papers.


What is the future of AGI?

  • Machines outperform humans in every physical task today and AGI may lead to AI “machines” bettering humans in many intellectual or mental tasks.
  • Bleak scenarios of super-intelligent machines enslaving humans have been imagined.
  • AGI systems could be a superior species created by humans outside of evolution.
  • AGI will indeed be a momentous development that the world must prepare for seriously.


Where the dangers lie?

  • Superhuman AI: The danger of a super intelligent AI converting humans to slaves.
  • Malicious humans with powerful AI:
    • AI tools are relatively easy to build.
    • LLMs can generate believable untruths as fake news and create deep mental anguish leading to self-harm.
    • Public opinion can be manipulated to affect democratic elections.
    • AI tools work globally, taking little cognancy of boundaries and barriers.
    • Individual malice can instantly impact the globe.
    • Governments may approve or support such actions against “enemies”.
  • Highly capable and inscrutable AI:
    • They may end up harming some sections more than others unintentionally, despite the best intentions of their creators.
    • These systems are created using Machine Learning from data from the world and can perpetuate the shortcomings of the data.
    • They may introduce asymmetric behaviors that go against certain groups.
    • Camera-based face recognition systems have been shown to be more accurate on fair-skinned men than on dark-skinned women.
      • Such unintended and unknown bias can be catastrophic in AI systems that steer autonomous cars and diagnose medical conditions.
    • Privacy is a critical concern as algorithmic systems watch the world constantly.
      • Every person can be tracked always, violating the fundamental right to privacy.
    • Who develops these technologies and how:
      • Most recent advances took place in companies with huge computational, data, and human resources.
      • Commercial entities with no effective public oversight are the centers of action.
        • Example:ChatGPT was developed by OpenAI which began as a non-profit and transformed into a for-profit entity.


Uses of AI:

  • AI can simulate the potential effects of laws.
    • For example, various datasets such as the Census, data on household consumption, taxpayers, beneficiaries from various schemes, and public infrastructure can be modeled.
  • AI can uncover potential outcomes of a policy.
  • It can also help in flagging laws that are outdated in the present circumstances and which require amendment.
    • For example, ‘The Epidemic Diseases Act, 1897’ failed to address the COVID-19 pandemic situation when the virus seemed to have overwhelmed the country.


Ethical Issues with AI:



Way Forward

  • Everything that affects humans significantly needs public oversight or regulation.
  • AI systems can have a serious, long-lasting negative impact on individuals.
  • We need to talk more about the unintentional harm AI may inflict on some or all of humanity.
    • These are solvable, but concerted efforts are needed.
  • India: We need systematic evaluation of western efficacy and shortcomings in Indian situations.
  • We need to establish mechanisms of checks and balances before large-scale deployment of AI systems.
  • AI holds tremendous potential in different sectors such as public health, agriculture, transportation and governance.
    • As we exploit India’s advantages in them, we need more discussions to make AI systems responsible, fair, and just to our society.
  • The European Union is on the verge of enacting an AI Act that proposes regulations based on a stratification of potential risks.
    • India needs a framework for itself, keeping in mind that regulations have been heavy-handed as well as lax in the past.



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