If you are a software engineer or a technology company, you’re probably wondering whether the government should regulate AI. There are a lot of questions surrounding this topic, but this article will provide a general overview of the Justifications for regulation, as well as the case for an entirely market-based approach. Ultimately, it’s up to you to decide which approach is right for you. The best way to make this decision is to be well informed, as AI is already changing our lives.
Justifications for regulation
A good reason to consider AI regulation is the potential for AI to be used in dangerous and unintended ways. While it may be tempting to tailor laws to AI, that is not the right approach. New technologies often raise questions of legal significance and create new fields of law. As previous technologies have shown, this approach can lead to unintended consequences. In this article, we’ll consider some of the key reasons to consider AI regulation.
First, regulatory measures should not allow AI to take advantage of the lack of privacy or security of human users. While we should embrace AI, we shouldn’t sacrifice our existing consumer protections. The White House has even issued guidance cautioning agencies against jettisoning “long-standing Federal regulatory principles.” A recent HUD draft of regulations could have led real estate developers to skirt existing fair housing laws. Regulations could protect consumers while protecting the public’s trust in AI.
Regulatory measures should be based on the impact of the AI technology on society. While governments have regulated novel technologies in the past, they have mostly been successful in protecting their citizens. The automobile, railroad technology, and telegraph were just some examples of technologies regulated by governments. AI systems are also tools used by humans, and their impacts will be based on how they’re used and by whom. The bipartisan group for AI regulation recommends a mild regulatory framework. If we can keep this in mind, AI regulations will have a more positive impact on the future of society.
As AI gains popularity, financial institutions will increasingly use AI to evaluate credit worthiness of millions of consumers. AI technologies typically involve the use of models that help lenders evaluate more information about credit applicants. Providing more information to lenders could increase efficiency and reduce the cost of credit. However, AI may also introduce risks such as privacy, illegal discrimination, and lack of transparency. Further, AI can cause inaccurate predictions due to bias in source data and in the construction of the models.
Justifications for a market-oriented approach to regulation
Many organizations and businesses rely on AI for strategic decisions, including heart attack risk prediction. These algorithms are largely opaque, with multiple layers of complexity. Even those who make them cannot explain their inner workings. A market-oriented approach to regulation could give them a leeway to experiment and adapt. This is why AI regulation should follow the same principles as other emerging technologies. In the long run, these new technologies could help our economy, but only if we regulate them responsibly.
AI has enormous potential for improving access to credit and lowering the cost of credit. It can be used to evaluate creditworthiness of millions of consumers. Lenders can now use the information collected to make more accurate predictions using AI-based models. AI has the potential to increase efficiency and lower the cost of credit, but it also poses risks of privacy and unlawful discrimination. AI algorithms are likely to make errors, and bias in the source data could make predictions inaccurate.
Emerging technologies have created new ways for consumers to interact and disrupt business models. Smart devices can anticipate consumer demands and make decisions based on that data. This new technology demands that regulators adapt quickly to protect citizens while ensuring fair and competitive markets. In this context, the role of regulators is vital to preserving the balance between innovation and consumer protection. While governments need to ensure a level playing field for innovative businesses and consumers, they should also consider the unintended consequences of disruption.
Alternatively, regulators may prefer a self-regulated approach to regulation. This is more desirable for companies because they can profit from selling customers’ information. In contrast, regulators may be more reluctant to regulate technology because their customers lack the knowledge and expertise to monitor bad practices. Self-regulation may be more efficient, but it may also hurt other parties in the industry. For example, it could prevent the industry from taking advantage of personal information.
Justifications for regulation in existing sectors
Regulatory reform will have to address these issues. The implications of AI in the financial sector are different from those in the healthcare sector. Using AI medical devices poses a life-threatening risk, and its application in healthcare must be regulated. Nevertheless, the draft Regulation touches on these issues, focusing on the high-risk nature of medical AI. It also requires the creation of a new classification system for AI medical devices.
There is also a risk of fundamental rights being violated by AI technologies. Ex post transparency is not enough to prevent fundamental rights from being violated. The aim of law is to protect citizens and prevent harmful practices. The use of AI in judicial decision-making should be based on adequate explanations and consent, and the production of AI should be transparent and accountable. However, the argument for regulating the use of AI in existing sectors is weak.
As AI systems become more sophisticated, they will change power dynamics. As a result, talk of an AI race has become common. Weaponized AI will have the potential to empower non-state actors and lower the threshold for war. Several countries have already outlined national AI strategies. Global governance will be necessary to ensure that AI is used in a beneficial and safe manner, and reduce risks to national and global security.
Regulation is needed for all sectors of AI, and AI medical devices are not an exception. Regulation must ensure that AI devices can be used in a scientifically valid manner and that their outputs correlate to expectations. Regulators must monitor AI medical devices and ensure they do not harm humans. However, regulating AI in medicine is difficult, and the FDA is keen to avoid causing unnecessary harm to patients. In addition to these concerns, the draft regulation will require manufacturers to pledge to transparency.
Justifications for regulation in new sectors
AI is a rapidly-growing technology with many possible applications, but there is no clear-cut regulation of AI. This technology may require sector-specific regulation, if it is to be widely adopted. The lack of regulation of AI is a symptom of a systemic failure to address the risks posed by new technologies. Developing an adequate AI policy, however, requires regulatory insight. Without an understanding of AI’s many challenges, policy may be counterproductive or ineffective.
New technologies and applications of AI are highly dynamic and complex, requiring a new regulatory framework. There are many unknown risks in this new technology and a regulatory mandate can’t control those risks. While some commentators have proposed creating a general AI regulator, this is unlikely to be successful until we understand the risks. Furthermore, it is unlikely that a regulatory mandate can be designed based on speculative risks.
Moreover, the ability of AI to continuously learn could result in algorithms that discriminate against humans. If AI is allowed to learn without oversight, it could become dangerous for users. Therefore, regulators should wait until the risk is known and evolvable, when it becomes clearer which activities should be regulated. That way, a policy can be formulated that will help people cope with AI.
Similarly, governments should consider implementing consistent AI approaches across sectors. Doing so can circumvent trade barriers and strengthen government oversight. Enforcing similar regulation by multiple governments increases the chances of catching international businesses. Such regulatory frameworks can also send a clear signal to civil society and academic communities and guide research toward shared concerns. This approach should be pursued as a governing principle for the future of AI.
Regulation of AI-related processes can also add to operational costs. For example, companies may need to create new sentinel roles and processes to monitor autonomous AI processes. In addition, the government may need to extend the mandate of its chief risk officer to monitor these autonomous AI processes. In addition, AI-related risks are not sufficiently documented. Further, companies may find themselves in the need to regulate their AI processes to protect against misuse.
