TITLE: ARTIFICIAL INTELLIGENCE AND LIABILITY LAWS

ABSTRACT:

This paper talks about a recent issue faced by a large number of members due to the one of the most rapidly evolving field named as “Artificial Intelligence”. Issues such as data privacy, intellectual property rights, and liability for AI-generated errors pose significant legal challenges. It discusses about which law would apply, or whether criminal or civil liability could ever apply and to whom it will apply, or whether the tort of negligence will apply. As, the technology AI grows rapidly into diverse sector including healthcare, finance, transportation, and entertainment, security, marketing education, finance, customer service. This is not an exhaustive list, and AI has many more potential applications in various domains and industries. With the rapid growth, it brings various complications and challenges in the field of legal landscape.

This paper delves into the relationship between the law and AI, with legal frameworks, liabilities, implications, concerns and recent issues in this field. The study ends with its benefits and dangers and explore flexible courses on how can we use by avoiding these challenges with foresight and integrity, we can harness the power of AI to build a more just, equitable, and accessible legal system for all, by examining case studies, existing laws and forecasting future developments.

KEYWORDS:

Artificial intelligence, legal frameworks, law & technology, privacy, Intellectual property rights.

INTRODUCTION:

Before leading to the legal frameworks, legal liability and the issue raised first, it is important to establish what this paper means by the term “artificial intelligence”. the term “AI” describes a wide range of technologies that power many of the services and goods we use every day- through apps, chatbots etc. The main focus of artificial intelligence is towards understanding human behaviour and performance.

It basically means the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. It refers to that computer system which are able to perform the complex tasks which human can do.

Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing.

RESEARCH METHODOLOGY:

Doctrinal Method of study, used secondary sources to write this paper on Online Dispute Resolution. Pre-existing research papers, articles, blogs, Journals and websites are some of the examples of secondary sources which are used to gather all the information provided in this research paper.

REVIEW OF LITERATURE:

There are some articles and papers on Artificial Intelligence and Liability laws available online like “The law and economics of AI liability” and Artificial Intelligence and Legal Liability”. These articles explore many fields like Safety Regulation, Efficient Liability Rules, Characteristics of AI, Types of Risk, who should be liable, Consideration for Efficient Liability Rules.

This review of literature provides a comprehensive overview of AI, covering its definition, types of Risks, benefits, challenges, legal frameworks, and prominent case laws. It synthesizes existing knowledge about AI and sets the stage for further exploration and analysis in the research paper.

Why is artificial intelligence important?

AI evaluates deeper data- AI analyses more and deeper data using neural networks that have many hidden layers.

It adds Intelligence- Artificial Intelligence has pushed the boundaries of the way computer machines used to operate and functions to make human lives easier.

Avoid Human errors- AI enabled computers make zero errors if programmed correctly.

Unbiased division- Machines have no emotions, unlike emotionally driven humans. AI thinks more practically and has a rational approach.

AI adapts through progressive algorithms- AI has all the skills and algorithms to process and make conclusions from big data in very less time.

Efficiency- Efficiency is the often-measurable ability to avoid making mistakes or wasting materials, energy, efforts, money, and time while performing a task.

Enhanced Customer Service- AI-powered solutions can help businesses to respond to customer queries and grievances quickly and address the situations,

ISSUES / CHALLENGES OF ARTIFICIAL INTELLIGENCE:

Artificial Intelligence has the potential to bring many benefits to society, but it also raises some important issues that need to be addressed, including:

Bias and Discrimination: AI systems can perpetuate and amplify human biases, leading to discriminatory outcomes.

Job Displacement: AI may automate jobs, leading to job loss and unemployment.

Lack of Transparency: AI systems can be difficult to understand and interpret, making it challenging to identify and address bias and errors.

Privacy Concerns: AI can collect and process vast amounts of personal data, leading to privacy concerns and the potential for abuse.

Security Risks: AI systems can be vulnerable to cyber-attacks, making it important to ensure the security of AI systems.

Ethical Considerations: AI raises important ethical questions, such as the acceptable use of autonomous weapons, the right to autonomous decision making, and the responsibility of AI systems for their actions.

Regulation: There is a need for clear and effective regulation to ensure the responsible development and deployment of AI.

MISUSE OF AI:

One of the biggest and most harmful examples of AI misuse are the so-called deepfakes. The term comes from a combination of “Deep learning” and “Fake media,” and it describes AI models that generate fake media, such as fake images, audio and videos. What began as an interesting research topic into AI, has become an enormous online problem.

Another famous misuse of artificial intelligence are AI-based password guessers, which are programs that continuously try to guess your password for several different websites and programs.

The possibility of AI violating existing intellectual property rights raises ethical and legal dilemmas. AI-based content creation can plagiarize or unintentionally violate copyrighted material, raising concerns about originality and fair use.

EXISTING LIABILITY RULES IN LAW:

The AI liability directive concerns ‘extra-contractual’ civil liability rules, i.e. rules providing a compensation claim irrespective of a contractual link between the victim and the liable person.

National liability rules offer different avenues to victims to claim compensation. A victim can make a

claim for damages caused by products and services based on a person’s conduct (‘fault-based liability’).

A fault-based claim usually requires proving the existence of damage, a fault of the liable person, and a causality between that fault and the damage. A victim can also make a claim for damage suffered irrespective of fault (‘strict liability’).

Under the PLD (no Fault-based Liability, Strict Liability), the victim can claim compensation for personal injury or damage to consumer property stemming from a defective product up to 10 years after such product is put into circulation.

As a result, three avenues for liability claims exist in the EU. The victim can seek compensation based on a fault-based liability claim (requires proving damage, fault and causality), on a strict liability Artificial intelligence liability directive 3 claim (independent of fault), or on a claim against the producer of a defective product (victims must prove that the product was defective and the causal link between that defect and the damage).

Gaughran v. the United Kingdom, 2020,

LIABILITY ISSUES WITH AN ARTIFICIAL INTELLIGENCE OR CONCERNS REGARDING EXISTING LIABILITY RULES:

The Commission concludes that this compensation gap could undermine citizens’ trust in AI, as well as the ability of the legal and judicial system to ensure fair and equitable results in claims involving AI systems. The implication is that creators of AI software or hardware aren’t liable for any injuries as long as these products were non-defective when made. That being said, defectively made AI, or AI that is modified by a licensee and causes damages as a result, can create liability for both the licensor and/or license.

SUGGETIONS TO AVOID CHALLENGES/ ISSUES CREATED BY AI:

The steps to overcome the challenges of AI include, ensuring high quality of data, data must be representative of the problem to be solved, careful selection of algorithms, ensure good computing power, ensure AI models can continuously learn and adapt to changing environments and data.

CONCLUSION:

As AI technologies enter everyday products and services, they are bound to play a role in liability lawsuits as well. This raises the question of whether liability rules are apt to deal with AI. This paper identified several possible gaps in liability rules, analysed the efficient liability regime for AI, and evaluated the recent EU proposals for producer and operator liability.

The paper identified the Meaning of AI, Why AI is important in recent time, The issues/ challenges faced by large number of populations, Misuse of AI, Existing Liability rules in law, concerns regarding the rules & lastly suggestion avoid these challenges/issues raised by AI. we use by avoiding these challenges with foresight and integrity, we can harness the power of AI to build a more just, equitable, and accessible legal system for all, by examining case studies, existing laws and forecasting future developments.

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