Good and bad – Generative artificial intelligence (AI) and its negatives| 3rd June 2023 | UPSC Daily Editorial Analysis

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What's the article about?

  • It talks about the applications, positives, and negatives of generative AI in the Indian context.


  • GS3: Awareness in the fields of IT, Space, Computers, Robotics, Nano-technology, Bio-technology and issues relating to Intellectual Property Rights;
  • Essay;
  • Prelims


  • Due to the development of OpenAI's ChatGPT chatbot, the technology of generative AI is constantly in the news.
  • Though this technology is quite useful, its negatives such as its ability to falsify data has raised some concerns regarding it.
  • Thus, India needs to harness the benefits of AI while avoiding adverse effects.

What is generative AI?

  • Generative AI (GenAI) is a type of Artificial Intelligence that can create a wide variety of data, such as images, videos, audio, text, and 3D models.
  • It does this by learning patterns from existing data, then using this knowledge to generate new and unique outputs.
  • GenAI is capable of producing highly realistic and complex content that mimics human creativity, making it a valuable tool for many industries such as gaming, entertainment, and product design.
  • Recent breakthroughs in the field, such as GPT (Generative Pre-trained Transformer) and Midjourney, have significantly advanced the capabilities of GenAI.
  • These advancements have opened up new possibilities for using GenAI to solve complex problems, create art, and even assist in scientific research.

What are the negatives of Generative AI?

  • Need for Quality Control and Data Accuracy:
    • One of the main disadvantages of Generative AI is that the data or content a particular model generates or produces still needs to be inspected and audited.
    • There are several instances in which a particular model has produced low-quality outputs that showed inaccuracies, lack of relevance, and questionable results, among others.
  • Ethical and Legal Issues and Considerations:
    • Issues about infringement of intellectual property rights such as copyrights and trademarks have emerged. Remember that Generative AI models are trained using large datasets.
    • These training sets are scrapped from the internet. The contents produced by text, image, and music generators are based on previous works of other creators and artists.
    • Using a Generative AI service can expose an individual or organization to potential legal responsibilities. For instance, besides intellectual property infringement, a specific service may generate new data that could potentially violate privacy rights.
  • Complexity and Technical Challenges:
    • Another disadvantage of Generative AI is that the technology in itself can be difficult to understand.
    • A lot of people do not know how it works and how to use or implement it. This can be counterproductive to its advantages and applications.


  • Dangers of AI: its ability to falsify data.
    • The world is past being able to reliably differentiate between data that faithfully reflects reality and data made to look that way by bad-faith actors using AI.
    • Dishonest actors wielding AI are one of many threats, but the statement is too simple to admit the complexity of human society.
  • Some specific concerns:
    • the inscrutability of the inner workings of AI models, their use of copyrighted data, regard for human dignity and privacy, and protections from falsifying information.
    • The models being developed and used today are not mandated to tick these boxes, even as there is no way to understand the risks they pose.
  • Proper policy solutions required:
    • So, even at a point when the computational resources required to run AI models in full coincide with those available in consumer electronics, the world will need at least rolling policies that keep the door open for democratic institutions to slam the brakes on dangerous enterprises.

Way Forward:

  • At this time, the Indian government should proactively launch and maintain an open-source AI risk profile, set up sandboxed R&D environments to test potentially high-risk AI models, promote the development of explainable AI, define scenarios of intervention, and keep a watchful eye.
  • Inaction is just not an option: apart from the possibility of adverse consequences, it could render India missing the ‘harnessing AI for good’ bus.

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