AI, Machine Learning, and Big Data: Laws and Regulations

Introduction to AI, Machine Learning, and Big Data Laws and Regulations

AI, big data, and machine learning have witnessed exponential growth over the past few years. With the evolving technology, businesses realize the importance of adopting AI and big data in their operations. AI, big data, and machine learning create exciting new opportunities for companies and entrepreneurs. But this rapid adoption is also partnered with several complexities and risks, hence, comes the need for regulations.

Regulators and policymakers find it difficult to keep track of the constant developments in technology and AI systems. Regulators on the global governance level are trying to keep themselves updated with the growing number of AI developments to ensure the laws and regulations stay relevant with new challenges and inventions.

The regulations define the enhancement of the public sector policies and laws for the use and promotion of AI, big data, and machine learning technologies. The laws and regulations are mandatory to manage the associated risks with AI and big data. The primary approach of these regulations is towards the financial and technical implications of the use of AI. The focus is on the underlying AI technologies like machine learning algorithms, big data analytics, the level of data input, insights, algorithm testing, and others alike.

How AI, Big Data, and Machine Learning are currently regulated?

The advancement of artificial intelligence technologies and the evolution of big data analytics and machine learning algorithms have pushed AI developers to implement the regulations to protect the ownership and rights attached to the AI applications.

There are several AI applications used in industries like defense, healthcare, business, education, insurance. A traditional approach towards regulating these ownerships and rights would prove inefficient. However, some of the existing laws and regulations for AI applications in India include:

1. The Copyright Right (1957) – According to this law, both the 'source code' and the 'object code' of an AI application will be protected as literary works. The developer of the AI application is considered as its owner, except, when the developer creates the application in the capacity of another employee during the term of employment. This act also ensures fair use and reverse engineering.

2. The Patents Act (1970) – According to section 3(k) of this law, computer programs are not subjected to patents. AI applications can be patented provided it is concerned with the development of a new AI application, along with the hardware. It is also mandatory to prove that both the software and hardware of the application are essential contents for the invention.

 Big data and data analysis has helped several companies to grow in the competitive market. Big data analysis involves thorough research with the help of machine learning algorithms, to draw insights from massive amounts of information and develop strategic courses of action to develop and amplify the growth of the business. Since big data revolves around the quality of data sources, anti-trust issues, consumer information, etc. there are several risks and complexities around its privacy policies.

Currently, no jurisdiction in the world has been able to devise regulatory laws concerning big data. Although in the United States, any company interested in engaging in big data activities and machine learning must observe the specified sector policies that apply to the different businesses. These policies protect the data involved in business operations and other business contracts.

Machine Learning involves deep neural networks and statistical analysis. These algorithms provide real-time results and are also prone to risks. The regulation for machine learning algorithms is necessary since it impacts the accuracy of its results. The AI model's performance is dependent on the validity of the data sources and the process for the collection through machine learning and data analysis.

It is acknowledged that there are several challenges and risks involved while implementing AI, big data, and machine learning in industrial operations. The use of AI tools and applications gives a competitive advantage to companies. In the years to come, AI will grow and jurisdictions around the world will devise regulations to ensure smooth functioning of the business operations as well as protect the rights and ownership concerns regarding these tools and applications.