Navigating Legal Challenges In AI
AI has been a buzzword in the tech industry and beyond in recent times, and many breakthroughs have been linked to it or involve it. However, as more breakthroughs in AI come to the fore, the legal side of things is also beginning to gain more attention. This article provides an in-depth exploration of the relationship between AI developments and the law, with a targeted focus on the intersection of AI and legal challenges.
Legal Framework For AI
There is no questioning the fact that AI is the next big thing for technology and human existence as a whole. However, it should be said that, just like every piece of groundbreaking technology, AI tech has to be properly regulated to prevent it from doing more harm than good. In recognition of this, governments all over the world have begun to take AI regulation very seriously. Let’s take a closer look at the current situation of AI and legal systems in different areas.
What Are The Areas In Which AI Can Face Legal Issues?
Intellectual Property
Intellectual property systems are designed to safeguard human innovation and grant them exclusive control over their creations. It’s also important to mention that IP laws are primarily focused on guiding creativity. According to a particular survey, over 81.5% of AI users employ the technology for various forms of content creation. In addition to this, AI-generated creative content like photos, videos, and others is becoming more and more popular in mainstream arts and entertainment. An excellent example is AI art crafted by tools like Midjourney and DALL-E.
Remember that IP systems have protection laws designed to benefit creators. So, this raises the question of who retains the fundamental right or control over AI-generated content. Can AI itself claim ownership rights to the content it generates, or does ownership automatically revert to the human behind the scenes?
There is another angle to this argument regarding intellectual property and AI. Generative AI tools only appear to create new things from scratch, but in reality, that’s not the case at all. These AI platforms actually generate images derived from their data pools, piecing already existing content into unique formats. This, of course, is a somewhat risky process that could lead to unintentional IP infringement, creating more legal problems. Then, there’s also the problem of protecting AI trade secrets and proprietary algorithms.
Currently, the laws guarding the intellectual property of AI-generated content are not favorable, since the law doesn’t currently recognize Artificial Intelligence as a legal entity. Because of this, no AI can claim IP rights for the creative content they generate. That said, there is currently a lot of conversation going on about AI and IP law at the World Intellectual Property Organization (WIPO).
Privacy And Data Protection
AI and Big Data have a complex, tightly-knit relationship. This is primarily due to the fact that for Artificial Intelligence to operate the way it does, it needs to gather and analyze tons of data. AI tools are usually designed to learn and continuously evolve as they become more exposed to increasing amounts of data. Because of this, AI is now seen as a double-edged tool where privacy is concerned.
Privacy is a pretty big concern in the world today, and there are currently lots of strict regulations about the collection and handling of data. However, AI tools and products challenge these strict guidelines.
Firstly, AI tools handle data in ways that are against regulations, storing and referring back to it for long periods of time. In addition to this, AI data collection goes way beyond public data to include even more personal information. This has, in turn, raised a lot of questions, especially regarding what exact information AI is collecting, how it is processing it, and who has access to stored personal data. Unfortunately, currently available data laws do not offer relief to users since they can’t even provide answers to privacy protection loopholes that AI currently exploits.
Liability And Accountability
The liability argument is one of the biggest areas of contention concerning AI. Let’s consider the event of a car accident involving a self-driving car and another regular car or pedestrian. Who bears the liability for the accident? Is the owner of the autonomous car liable for the car collision, or does responsibility for the accident fall back to the car manufacturer? These are pertinent questions that existing regulations simply do not provide satisfactory answers to.
Currently, there are several proposed suggestions aimed at providing a permanent and impactful answer to AI liability and accountability issues. One school of thought suggests that liability should transfer back to the person operating the tool at the time the issue occurred. Another one talks about the possibility of proactive monitoring. Here, users are tasked with documenting and reporting any liabilities that occur because of an AI-linked breach. This reporting should then be followed up by interventions from legal and external compliance teams.
Ethical Considerations
It’s not possible to explore the ethical considerations and limitations of AI tools without first talking about bias and fairness in AI. AI tools are by nature regarded as impartial and highly accurate decision-makers on several issues. However, biases can arise in these systems, especially regarding healthcare, criminal justice, and something as seemingly basic as facial recognition.
These biases occur primarily because of defects in the source data used for AI training and evolution. Defects in source data primarily arise from “poisoned data pools,” meaning data containing biased or incomplete information. When biases occur in AI systems, they unavoidably result in violations of fundamental human rights in various demographics.
Another aspect of ethical consideration limitations in AI systems usually occurs when they are faced with a seemingly impossible choice. For example, in the case of AI-powered vehicles facing unpreventable accident situations, how does the AI choose what sacrifice to make? In these situations, does the AI system prioritize the lives inside the car or those outside of it?
Because of all these questions and ambiguities surrounding AI ethical guidelines, there is a lot of talk surrounding creating ethical AI development tools. One of these involves using fairness metrics like demographic parity [1], equalized odds, and individual fairness. Aside from this, there are also some guidelines in place for regulating AI fairness, albeit not directly. An excellent example is the Equal Credit Opportunity Act (ECOA) [2]. The ECOA is a piece of legislation that governs how AI should be used in credit scoring. It strongly frowns on using AI to discriminate against people based on their color, nationality, and even age.
Conclusion
From all that has been explored so far, it’s evident that there are numerous legal challenges regarding AI development and utilization currently. Although governmental bodies like the European Union (EU) are already proposing legal checks for AI, the much-needed full implementation is still some steps away.
Further Reading:
[1] AI And Fairness Metrics: Understanding And Eliminating Bias [2] AI Lending And ECOA: Avoiding Accidental DiscriminationÂSource link
