Can Computers Create Art?

This essay discusses whether computers, using Artificial Intelligence (AI), could create art. First, the history of technologies that automated aspects of art is surveyed, including photography and animation. In each case, there were initial fears and denial of the technology, followed by a blossoming of new creative and professional opportunities for artists. The current hype and reality of Artificial Intelligence (AI) tools for art making is then discussed, together with predictions about how AI tools will be used. It is then speculated about whether it could ever happen that AI systems could be credited with authorship of artwork. It is theorized that art is something created by social agents, and so computers cannot be credited with authorship of art in our current understanding. A few ways that this could change are also hypothesized.Comment: to appear in Arts, special issue on Machine as Artist (21st Century

Platforms, the First Amendment and Online Speech: Regulating the Filters

In recent years, online platforms have given rise to multiple discussions about what their role is, what their role should be, and whether they should be regulated. The complex nature of these private entities makes it very challenging to place them in a single descriptive category with existing rules. In today’s information environment, social media platforms have become a platform press by providing hosting as well as navigation and delivery of public expression, much of which is done through machine learning algorithms. This article argues that there is a subset of algorithms that social media platforms use to filter public expression, which can be regulated without constitutional objections. A distinction is drawn between algorithms that curate speech for hosting purposes and those that curate for navigation purposes, and it is argued that content navigation algorithms, because of their function, deserve separate constitutional treatment. By analyzing the platforms’ functions independently from one another, this paper constructs a doctrinal and normative framework that can be used to navigate some of the complexity. The First Amendment makes it problematic to interfere with how platforms decide what to host because algorithms that implement content moderation policies perform functions analogous to an editorial role when deciding whether content should be censored or allowed on the platform. Content navigation algorithms, on the other hand, do not face the same doctrinal challenges; they operate outside of the public discourse as mere information conduits and are thus not subject to core First Amendment doctrine. Their function is to facilitate the flow of information to an audience, which in turn participates in public discourse; if they have any constitutional status, it is derived from the value they provide to their audience as a delivery mechanism of information. This article asserts that we should regulate content navigation algorithms to an extent. They undermine the notion of autonomous choice in the selection and consumption of content, and their role in today’s information environment is not aligned with a functioning marketplace of ideas and the prerequisites for citizens in a democratic society to perform their civic duties. The paper concludes that any regulation directed to content navigation algorithms should be subject to a lower standard of scrutiny, similar to the standard for commercial speech

Cashless Societies and the Rise of the Independent Cryptocurrencies: How Governments Can Use Privacy Laws to Compete with Independent Cryptocurrencies

Many individuals (including governments) envision living in a future world where physical currency is a thing of the past. Many countries have made great strides in their efforts to go cashless. At the same time, there is increasing awareness among citizens of the decreasing amount of privacy in their lives. The potential hazards cashless societies pose to financial privacy may incentivize citizens to hold some of their money in independent cryptocurrencies. This article argues that in order for governments in cashless societies to keep firm control over their money supply, they should enact stronger privacy law protections for its citizens in order to decrease the real or perceived loss of (financial) privacy. This paper compares the privacy laws that exist today in both the United States and the European Union and suggests combining elements of both legal systems in order create a more privacy-friendly legal framework that can enable governments to complete against independent cryptocurrencies

What is an Analogue for the Semantic Web and Why is Having One Important?

This paper postulates that for the Semantic Web to grow and gain input from fields that will surely benefit it, it needs to develop an analogue that will help people not only understand what it is, but what the potential opportunities are that are enabled by these new protocols. The model proposed in the paper takes the way that Web interaction has been framed as a baseline to inform a similar analogue for the Semantic Web. While the Web has been represented as a Page + Links, the paper presents the argument that the Semantic Web can be conceptualized as a Notebook + Memex. The argument considers how this model also presents new challenges for fundamental human interaction with computing, and that hypertext models have much to contribute to this new understanding for distributed information systems

“You Keep Using That Word”: Why Privacy Doesn’t Mean What Lawyers Think

This article explores how the need to define privacy has impeded our ability to protect it in law. The meaning of “privacy” is notoriously hard to pin down. This article contends that the problem is not with the word “privacy,” but with the act of trying to pin it down. The problem lies with the act of definition itself and is particularly acute when the words in question have deep-seated and longstanding common-language meanings, such as liberty, freedom, dignity, and certainly privacy. If one wishes to determine what words like these actually mean to people, definition is the wrong tool to use. The exact wrong way to go about understanding privacy is by supplying one’s own definition; that is unscientific. Since words in a living language mean many things (e.g., what does “cool” mean?), the act of definition reduces the multiple meanings of the defined word to a specified meaning. Each increase in precision comes with a corresponding separation from some set of meanings that would have applied to the living, undefined version of the word. The resulting defined word may be more precise but is often crippled, isolated, and bereft of the connections and connotations that made it part of a rich and living language. Like Procrustes, who strapped his victims to a bed and then either lopped off their feet if they stuck out or stretched the person on a rack if they were too short, lawyers are specifically trained to stretch and cut words. Tools of definition are badly suited to determine what people mean when they say “privacy.” For example, the actual meaning of “privacy” might better be explored through the tools of linguistics or cultural anthropology than through the tool of legal definition. This article therefore recommends that lawyers should set aside the flawed tool of definition and pick up the tool of analogy when they ask what words like privacy mean. This article asks why privacy has been uniquely pressed by concerns about supposed imprecision. For example, we do not stop our search for “security” because of a supposed lack of definition of the word. If privacy must have a definition to be operationalized, it will remain be conveniently narrow. moribund. And if privacy requires narrowing to be operationalized, any operationalization will be conveniently narrow. “You keep using that word. I do not think it means what you think it means.

Privacy as a Public Good

Privacy is commonly studied as a private good: my personal data is mine to protect and control, and yours is yours. This conception of privacy misses an important component of the policy problem. An individual who is careless with data exposes not only extensive information about herself, but about others as well. The negative externalities imposed on nonconsenting outsiders by such carelessness can be productively studied in terms of welfare economics. If all relevant individuals maximize private benefit, and expect all other relevant individuals to do the same, neoclassical economic theory predicts that society will achieve a suboptimal level of privacy. This prediction holds even if all individuals cherish privacy with the same intensity. As the theoretical literature would have it, the struggle for privacy is destined to become a tragedy. But according to the experimental public-goods literature, there is hope. Like in real life, people in experiments cooperate in groups at rates well above those predicted by neoclassical theory. Groups can be aided in their struggle to produce public goods by institutions, such as communication, framing, or sanction. With these institutions, communities can manage public goods without heavy-handed government intervention. Legal scholarship has not fully engaged this problem in these terms. In this Article, we explain why privacy has aspects of a public good, and we draw lessons from both the theoretical and the empirical literature on public goods to inform the policy discourse on privacy