INDUSTRY 4.0 AND LAW : A DIALECTIC RELATIONSHIP
The interface between law and technology has been summarized in the golden words of Daniel J. Giff ord, “ Law and technology interact when legal rules foster or retard the development of technology. They also interact when society decides that technology produces undesirable results and employs legal rules to contain or modify those results”. Law, as we are aware, is a set of pre-set rules meant for the purpose of keeping peace and security in society. It is a social engineering which means a balance between the competing interests in society. Technology, on the other hand means the use of scientifi c knowledge for practical purposes or applications, whether in industry or in our everyday lives. Needless to say, the interface of each of these technologies with the legal framework is complex. The internet infrastructure itself raises myriad legal concernsICANN jurisdiction, competition law and policy, network neutrality, infrastructuresharing and interoperability being the major ones. Similarly AI – powered devices come with a range of challenges, particularly on the fault front. The real dilemma associated with autonomous cars is – who is liable for damages resulting from accidents- maker or machine. Of course, suggestions have been put forth as to how liability of robots can be determined. These range from strict-liability approach (no fault required) to risk management approach (liability of a person who was able to minimize the risks). The legal community is also largely unanimous that liability of robots should be proportionate to the actual level of instructions given to the robot and its degree of autonomy. However, the crux of the issue with A1– powered devices is that as increasingly the decisions that they take become more and more removed from any direct programming and are in turn based more on machine learning principles, it becomes harder to attribute the question of fault . Herein lies the importance of AI governance – the goal of which is to minimize potential risks from bias and maximize intended benefits. In particular, the legal framework must ensure that AI is a. fair and impartial b. transparent and explainable c. responsible and accountable d. safe and secure e. compliant with data and privacy regulations as well as f. robust and reliable. In the Indian context, the focus must be on attuning the legal system to the pillars of AI governance ( viz ) AI IP and innovation, AI compute and systems, Skilling in AI, Data for AI and AI ethics. One must be all the more careful about generative AI which can introduce falsehoods into the copy it produces and bias into the text it generates. Needless to say, deep fakes form a big source of concern. They are the manipulations of facial appearance through deep generative methods. As they leverage powerful techniques from machine learning & AI to manipulate or generate visual and audio content that can easily deceive, dealing with the legal challenges posed by them is easier said than done. Internet and robotics are not the only innovations where growth of technology brings forth legal puzzles.