This workshop aims to address some of the insights that we have gained about the ethics of AI and the concept of trust. We critically explore practical and theoretical issues relating to values and frameworks, engaging with carebots, evaluations of decision support systems, and norms in the private sector. We assess the objects of trust in a democratic setting and discuss how scholars can further shift insights from academia to other sectors. Workshop proceedings will appear in a special symposium issue of C4eJournal.net. Speakers: Judith Simon (University of Hamburg), Can and Should We Trust ..read more

As the fabric of the city becomes increasingly fibreoptic, enthusiasm for the speed and ubiquity of digital infrastructure abounds. From Toronto to Abu Dhabi, new technologies promise the ability to observe, manage, and experience the city in so-called real-time, freeing cities from the spatiotemporal restrictions of the past. In this project, I look at the way this appreciation for the real-time is influencing our understanding of the datafied urban subject. I argue that this dominant discourse locates digital infrastructure within a broader metaphysics of presence, in which instantaneous dat ..read more

Oftentimes, the development of algorithms are divorced from the environments where they will eventually be deployed. In high stakes contexts, like child welfare services, policymakers and technologists must exercise a high degree of caution in the design and deployment of decisionmaking algorithms or risk further marginalising already vulnerable communities. This talk will seek to explain the status quo of child welfare algorithms, what we miss when we fail to include context in the development of algorithms, and how the addition of qualitative text data can help to make better algorithms. Kam ..read more

Many research and industry organizations outsource data generation, annotation, and algorithmic verification—or data work—to workers worldwide through digital platforms. A subset of the gig economy, these platforms consider workers independent users with no employment rights, pay them per task, and control them with automated algorithmic managers. This talk explores how the coloniality of data work is characterized by an extractivist method of generating data that privileges profit and the epistemic dominance of those in power. Social inequalities are reproduced through the data production pro ..read more

Teens have different attitudes toward AI. Some are excited by AI’s promises to change their future. Some are afraid of AI’s problems. Some are indifferent. There is a consensus among educators that AI is a “must-teach” topic for teens. But how? In this talk, we will share our experiences and lessons learned from the Imagine AI project, funded by the National Science Foundation and advised by the Center for Ethics (C4E). Unlike other efforts focusing on AI technologies, Imagine AI takes a unique approach by focusing on AI ethics. Since 2019, we have partnered with more than a dozen teachers to ..read more

Panelists: Kristen Thomasen, Suzie Dunn, & Kate Robertson This panel will discuss Citizen Lab and LEAF’s collaborative submission to the Toronto Police Services Board’s public consultation on its draft policy for AI use by the Toronto police with the three co-authors of the submission. The submission made 33 specific recommendations to the TPSB with a focus on substantive equality and human rights. The panelists will discuss some of those recommendations and the broader themes identified in the draft policy ..read more

No one has any doubt that the future of the economic system is digital. Central banks worldwide worry that the rising popularity and adoption of cryptocurrencies and other means of payments, and new financial instruments, pose a risk to early fintech adopters and the economy at large. As an alternative, most central banks worldwide, led by the Bank of International Settlements, consider the issuance of a CBDC (Central Bank Digital Currency) – the digital form of a country’s fiat money. A CBDC differs from existing cashless payment forms such as card payments and credit transfers: it represents ..read more

In the last years, legal scholars and computer scientists have discussed widely how to reach a good level of AI accountability and fairness. The first attempts focused on the right to an explanation of algorithms, but such an approach has proven often unfeasible and fallacious due to the lack of legal consensus on the existence of that right in different legislations, on the content of a satisfactory explanation and the technical limits of a satisfactory causal-based explanation for deep learning models. In the last years, several scholars have indeed shifted their attention from the legibilit ..read more

We are in the midst of ongoing debate about whether, in principle, the enforcement of legal rules—and corresponding decisional processes—can be automated. Often neglected in this conversation is the role of equity, which has historically worked as a particularized constraint on legal decision-making. Certain kinds of equitable adjustments may be susceptible to automation—or at least, just as susceptible as legal rules themselves. But other kinds of equitable adjustments will not be, no matter how powerful machines become, because they require non-formalizable modes of judgment. This should giv ..read more

Artificially intelligent agents that provide care for human beings are becoming an increasing reality globally. From disembodied therapists to robotic nurses, new technologies have been framed as a means of addressing intersecting labour shortages, demographic shifts, and economic shortfalls. However, as we race towards AI-focused solutions, we must scrutinize the challenges of automating care. This talk engages in a two-part reflection on these challenges. First, issues of building trust and rapport in such relationships will be examined through an extended case study of a chatbot intended to ..read more