AI and the Responsibility Gap

AI regulation is going to be very different from the regulation of any other tool created by humans. In the past, most human-made tools had one quirk: they could be understood by humans themselves. After all, tools of the past could not make themselves, and thus a human had to make the tool whilst understanding the tool in the process. A swordsmith understood his sword, just as a computer scientist understood her program. However, AI differs from this because autonomous AI is not a tool that needs to be created by a human. Instead, through unsupervised training, AI can be considered a tool that creates itself. Of course, initially the training needs to be set up by a human. But once it gets going, new forms of autonomous AI train themselves to get better, with no human understanding what is happening inside the "black box."

As early as 2004, philosophers like Andreas Matthias realized a problem that this could cause. The issue lies in how we normally regulate tools. Whenever we regulate a tool, like a car, there is a balance of responsibility taking place. Part of the responsibility is put on the user of the tool. After all, many car crashes are user error. However, since the creator of the tool (in the past) has the ability to understand the tool they are creating for people's use, there has also been an element of responsibility put on the creator. If a car is unsafe, the manufacturer has the ability to know and understand why it is unsafe courtesy of testing and other measures. Hence, when a car has a malfunction that is not due to user error, it is the fault of the manufacturer. The issue that AI introduces is that when creating AI, the creators of AI may not have the ability to understand what they are creating. Since the AI trains itself, and learns to adapt to situations the creators may never think of, it is almost impossible for the creators to test and know what the AI will do in certain situations.

Now, imagine an AI robot is performing surgery, and because every patient's body is different, an unexpected trigger occurs, causing the AI robot to go off course and harm the patient. In this situation, the hospital as the user doesn't bear much responsibility, since they were never told the AI could do something like this. At the same time, we cannot place responsibility on the coders because the coders also could have never known this could happen: the AI was training itself in new situations after all. As a result, a gap appears in the traditional frameworks for responsibility because clearly something bad has happened, and the need for responsibility has been frustrated. Surrounding this core issue, a whole literature has appeared. Some people say that the responsibility gap is a big deal, and that it must limit the extent to which AI can automate society. For example, we may concede that we can never have AI surgeons doing work without a human surgeon on hand to monitor it (while also acting as the responsibility fallback if something goes wrong). Others have argued that the AI responsibility gap is just a reframing of existing issues in assigning responsibility, such as the problem of many hands. Whatever the solution, AI will surely introduce ethical problems that will be key to understanding how to regulate and introduce the technology into society.

Dr. Matthias

Deborah Stone and Nuances of Public Policy

In her book Policy Paradox: The Art of Political Decision Making, Deborah Stone unpacks what it means to approach difficult policy problems. The book is largely a refutation of the positivist movement policy science, which Stone describes as solutions to policy problems through “rationalist” projects. To proponents that say data alone can be used to solve problems, Stone states that data can only solidify or weaken the specified impacts of a policy. It does nothing to decide if those impacts are beneficial, or even wanted. To illustrate this problem, Stone create the term “policy paradoxes.” These are policy situations where impacts can be both positive or negative, depending on the perspective of the stakeholder. As an example, Stone uses the policy of rubble removal following Hurricane Katrina. This was a policy paradox because the rubble removal was beneficial for many businesses, who needed to clear the streets quickly before reopening. However, it was also harmful for families, who didn’t want their possessions buried in the rubble to disappear forever. Stone’s point is that in situations like these, data cannot help us. Data can tell us how quickly the rubble removal can occur, but it does nothing to decide whose perspective carries the most moral and social importance. 

In this, Stone’s book does a good job of explaining the nuances of public policy. It shows how public policy can be value based, with stakeholder stories serving as data points in and of themselves. However, a problem is that the book doesn’t offer much in terms of a solution. The sentiment is: things are more complicated than we thought, and yes, that means we no longer have a secure solution for these issues. This brings up a larger question in policy studies as a whole. The more people learn about both complex issues and human nature, it almost feels like we are moving away from success. Previous solutions aren’t as good as we thought, and with some issues, there seems to be no solution at all.

Against this cynicism, an idea is that we don’t need perfect solutions at all. Perhaps if perfect solutions are impossible, considering the existence of policy paradoxes, policy analysis is still justified in the creation of marginal improvements. Whatever it is, Stone’s book is more of an analysis of current reality, rather than an explanation of potential future solutions. 

Philosophy In Public Policy

Public policy encompasses all the ways a government finds solutions to societal problems. As such, policy studies is the analysis of these solutions. Through data analysis and surveys, policy evaluation can help us understand the impacts of a policy. We can learn "what" policy does in the real world. Moreover, the study of public administration can help us understand the processes by which policies can be created. Through policy implementation, we see the "how" behind policy, and "who" is involved.

With the Agenda Setting and Policy Formation stages of the policy making process, we see a different dimension. This is when we ask, "why?" Why should one course of action be taken instead of another? Why do some beliefs conflict, while others seem to work in tandem? The conversation becomes one of ethics and morals, where ethics are the external beliefs and "rules" society sets for a conversation, and morals are the internal values that vary from personal to person.

As with any question, the interaction of ethics and morals shapes how we perceive and interact with policy. For example, a discussion on SBA loans may adopt a common ethical base of consequentialism, all the stakeholders may agree the best policy is the one that maximizes the utility between both businesses and tax payers. However, whether the small businesses utility or the taxpayer's utility is worth more becomes a moral issues. It will vary between different people, even if the ethical framework is the same.

Within this analysis, public policy philosophy is unique in the very definition of public, leading to a . Unlike the policy of a company or an NGO, public policy applies to everyone. As such, there is a whole philosophy of how the collective opinions of the public gets processed through public administration, and whether this process is correct to begin with. One can ask, if policy makers have access to superior information than the public, are they justified in going against moral judgements of an ill-informed majority? This question lives within the policy making process. More than that, its based in the wider philosophy of democracy and government, showcasing how even specific policy making questions are interdisciplinary at their core.

At the end of the day, within the current system, policy will still be most impacted by the political pressures what weigh on decision makers. However, systems of governance aren't static. The philosophy of public policy helps us understand why decisions in the current public policy process occur as they do, and in doing so it provides insights into how our system can and should change moving into the future.