Legal Challenges in the Emerging AI and Machine Learning Startup Arena

By Mr Sagar Aggarwal

Data protection is a significant concern across the world in the AI and ML systems. The integration of these advanced technologies often involves the collection, processing, and analysis of personal data, raising ethical considerations regarding privacy rights and data protection. With the right direction, an AI usage policy empowers every organization to leverage advanced technologies like AI and ML’s immense potential while managing the associated risks and responsibilities. 

In today’s era, the expanding usage of advanced technologies like artificial intelligence (AI) and machine learning (ML)in the emerging startups are creating several legal implications. Machine learning and artificial intelligence technologies possess the potential to revolutionize industries, such as finance, transportation, healthcare, etc. The legal issue in AI revolves around the complex interplay between existing legal doctrines and evolving advanced technology. These issues are primarily due to the AI systems, especially those based on generative technology, can perform tasks that were conventionally exclusive to humans, like editing, image generation, writing, etc.  AI Law encompasses a wide range of legal domains, such as contract law, tort law, intellectual property, and privacy law, all of which are being reshaped in the context of AI.

Various countries across the globe have taken numerous steps to address these limitations by enacting specific guidelines tailored to AI. For instance, the European Union’s General Data Protection Regulation (GDPR) provides provisions that are related to automated decision-making, with the objective of safeguarding individuals’ rights in the age of AI. Countries like the United States and Canada are working on various regulatory frameworks to address concerns related to AI bias, transparency, and accountability.

Ethical Consideration in Deployment of Machine Learning and Artificial Intelligence:

  • Privacy and Data Protection: AI and ML systems usually require vast amounts of data which raises concerns regarding user privacy, data protection, and user consent. Ensuring compliance with regulations like the GDPR (General Data Protection Regulation) is essential for startups deploying AI and ML solutions.
  • Liability and Accountability: When a generative AI model or advanced ML technology makes a decision that leads to harm, who is liable? The legal system faces challenges to attribute liability in such cases.
  • Transparency and Demonstrability: There is a rise in demand for legal requirements that AI systems be transparent, and their decisions can be explainable, especially in critical sectors including healthcare and criminal justice. This is a major challenge given the often ‘black box’ nature of AI algorithms.
  • Bias and Discrimination: AI and ML solutions can perpetuate and even intensify biases present in their training data. This results in legal concerns about discrimination and fairness, especially in areas like employment and lending.


Legal Provisions Governing AI in India

  1. Information Technology Act, 2000: The Information Technology Act, 2000 (IT Act) serves as the fundamental legislation governing electronic transactions and digital governance.
  2. Case Law: In the landmark case of Justice K.S. Puttaswamy (Retd.) v. Union of India (2017), the Supreme Court of India recognized the right to privacy as a fundamental right under the Indian Constitution. The primary aim of this right is to safeguard personal data from AI-based systems.
  3. Personal Data Protection Bill, 2019: The Personal Data Protection Bill, 2019 introduces principles and obligations for entities processing personal data, including data localization, accountability, consent, and purpose limitation.
  4. Indian Copyright Act, 1957: The Indian Copyright Act, 1957 protects original literary, artistic, musical, and dramatic works, granting exclusive rights to creators and prohibiting unauthorized use or reproduction.
  5. National e-Governance Plan: The National e-Governance Plan aims to digitally empower Indian society by providing online government services. Technology like AI plays a vital role in improving the efficiency and accessibility of e-governance.
  6. New Education Policy: The Indian government recently launched its New Education Policy (NEP), which includes provisions regarding special coding classes for students of the 6th standard. The government aims to establish India as the next innovation hub.
  7. AIRAWAT: Recently, Niti Ayog (planning commission of India) also launched AIRAWAT, which stands for AI Research, Analytics, and Knowledge Assimilation platform. It includes all the necessary requirements of AI in India


Government Initiatives to Protect Your Intellectual Property

An act in 1998 was introduced in the United States (US) to prohibit unauthorized access and exploitation of protected works on the Internet by applying two treaties of the World Intellectual Property Organization (WIPO). This was considered as a great initiative towards embracing intellectual property rights and integrating legal protection in the digital scenario.

There are various IP laws to secure digital publications and access rights of digitized archives.  In the United Kingdom (UK), Open Data Commons is a group that has launched a set of legal tools and database laws that control the accessibility and use of data sets. They have introduced numerous schemes to demarcate the public domain data from inaccessible versions of data. They reach this goal by classifying the several kinds of data depending on the extent to which the information can be accessed and employed by third parties with authorization and consent from the author.


The IP implications of AI-generated developments, including patenting, copyright, and trade secrets, imply various challenges that need to be addressed to foster innovation while protecting the rights of the developers. It is crucial to emphasize the importance of addressing algorithmic bias and ensuring fairness and non-discrimination in AI systems. Various strategies are implemented to mitigate biases and promote responsible data collection in building trustworthy and unbiased AI systems. Legal considerations play a crucial role in the deployment of AI and ML technologies. Aligning AI systems with societal values and norms and adopting ethical frameworks and principles, is significant to ensure responsible and ethical AI practices.


(The author is Mr Sagar Aggarwal, Managing Partner at Areness, and the views expressed in this article are his personal)