I wish them well.
Denver suburb won’t cough up millions in ransomware attack that closed city hall
John Aguilar reports:
The demand was big: $5 million to unlock Wheat Ridge’s municipal data and computer systems seized by a shadowy overseas ransomware operation.
The response was defiant: We’ll keep our money and fix the mess you made ourselves.
Read more at The Denver Post.
A very good ‘bad example.’
https://qmro.qmul.ac.uk/xmlui/handle/123456789/80559
Facial Recognition Technology vs Privacy: The Case of Clearview AI
In January 2020, the New York Times revealed the existence of Clearview AI, a company that had developed a facial recognition tool of unprecedented performance. Various actors were fast in declaring the loss of privacy accompanying the deployment of the application. This paper analyses how the economic motives behind facial recognition technologies challenge the established understanding and purpose of the fundamental right to privacy by the example of the EU. It argues that Clearview AI’s business model, based on the surveillance of the company’s data subjects, forcibly entails a violation of the latter’s fundamental right to privacy. The traditional vertical application of fundamental rights in cyberspace disregards the power asymmetry existing between private individuals and private companies with state-like power in the Digital Age, thus resulting in legal ineffectiveness in face of this violation. The author concludes that the most fruitful approach to safeguard privacy would be the horizontal application of the fundamental right to privacy.
Humans need to talk ethics to their AI.
https://link.springer.com/article/10.1007/s43681-022-00214-z
Ethics in human–AI teaming: principles and perspectives
Ethical considerations are the fabric of society, and they foster cooperation, help, and sacrifice for the greater good. Advances in AI create a greater need to examine ethical considerations involving the development and implementation of such systems. Integrating ethics into artificial intelligence-based programs is crucial for preventing negative outcomes, such as privacy breaches and biased decision making. Human–AI teaming (HAIT) presents additional challenges, as the ethical principles and moral theories that provide justification for them are not yet computable by machines. To that effect, models of human judgments and decision making, such as the agent-deed-consequence (ADC) model, will be crucial to inform the ethical guidance functions in AI team mates and to clarify how and why humans (dis)trust machines. The current paper will examine the ADC model as it is applied to the context of HAIT, and the challenges associated with the use of human-centric ethical considerations when applied to an AI context.
Easily understood. Most “AI” is aimed at very specific commercial goals, not broad ‘general intelligence’ issues.
Meta's AI guru LeCun: Most of today's AI approaches will never lead to true intelligence
Yann LeCun, chief AI scientist of Meta Properties, owner of Facebook, Instagram, and WhatsApp, is likely to tick off a lot of people in his field.
With the posting in June of a think piece on the Open Review server, LeCun offered a broad overview of an approach he thinks holds promise for achieving human-level intelligence in machines.
Implied if not articulated in the paper is the contention that most of today's big projects in AI will never be able to reach that human-level goal.
Interesting (appropriate?) application of facial recognition. Protecting Taylor Swift...
https://via.library.depaul.edu/cgi/viewcontent.cgi?article=4202&context=law-review
The Legal and Ethical Considerations of Facial Recognition Technology in the Business Sector
Anonymity is no longer possible since most individuals have photo identifications and social media posts with pictures available for public viewing. Surveillance methods also continue to develop, which has resulted in individuals being exposed to the greater use of facial recognition techniques without their awareness or permission. This system references equipment with the dual purpose of “connecting faces to identities,” and permitting the “distribution of those identities across computer networks.” The software is primarily employed for “identification and access control or for identifying individuals who are under surveillance.” This technology is premised upon the idea that their inherent physical or behavioral characteristics can be used to correctly recognize every individual.
Averaging ethics?
https://www.mdpi.com/2673-2688/3/3/45
Bridging East-West Differences in Ethics Guidance for AI and Robotics
Societies of the East are often contrasted with those of the West in their stances toward technology. This paper explores these perceived differences in the context of international ethics guidance for artificial intelligence (AI) and robotics. Japan serves as an example of the East, while Europe and North America serve as examples of the West. The paper’s principal aim is to demonstrate that Western values predominate in international ethics guidance and that Japanese values serve as a much-needed corrective. We recommend a hybrid approach that is more inclusive and truly ‘international’. Following an introduction, the paper examines distinct stances toward robots that emerged in the West and Japan, respectively, during the aftermath of the Second World War, reflecting history and popular culture, socio-economic conditions, and religious worldviews. It shows how international ethics guidelines reflect these disparate stances, drawing on a 2019 scoping review that examined 84 international AI ethics documents. These documents are heavily skewed toward precautionary values associated with the West and cite the optimistic values associated with Japan less frequently. Drawing insights from Japan’s so-called ‘moonshot goals’, the paper fleshes out Japanese values in greater detail and shows how to incorporate them more effectively in international ethics guidelines for AI and robotics.
(Related)
https://onlinelibrary.wiley.com/doi/full/10.1111/meta.12583
Flourishing Ethics and identifying ethical values to instill into artificially intelligent agents
The present paper uses a Flourishing Ethics analysis to address the question of which ethical values and principles should be “instilled” into artificially intelligent agents. This is an urgent question that is still being asked seven decades after philosopher/scientist Norbert Wiener first asked it. An answer is developed by assuming that human flourishing is the central ethical value, which other ethical values, and related principles, can be used to defend and advance. The upshot is that Flourishing Ethics can provide a common underlying ethical foundation for a wide diversity of cultures and communities around the globe; and the members of each specific culture or community can add their own specific cultural values—ones which they treasure, and which help them to make sense of their moral lives.
Backgrounders…
Data privacy and artificial intelligence (AI)
Artificial intelligence (AI) has disrupted the ways customers and firms interact. However, AI runs on data and, in the case of this chapter, customers’ personal informational data. Yet, even in the face of a new paradigm for AI and customers’ online behaviors, there is a need for clarification of key concepts and definitions in this domain. The main objective of this chapter is threefold. First to provide a concrete definition of data privacy which will conceptually drive this chapter. Second, we focus on the three popular types of AI in the marketing domain AI types prevalent (natural language processing, machine learning, and deep learning) and identify how they give way to AI data privacy issues. Third, this study will provide two case studies (Clearview AI and Hello Barbie) which document and explicate the means by which AI collects customer data and how this gives way to data privacy issues. Overall, this chapter will provide a conceptual alignment and understanding of the complex arena of AI and data privacy.
(Related)
Solutions to artificial intelligence (AI) and privacy
The main objective of this study is to understand the implications of artificial intelligence (AI) and its influence on data privacy. Via a series of case studies and discussions, this chapter strives to provide insights into data privacy issues facing marketers and customers in the digital space through their usage of AI. To achieve this, this chapter will align and extend AI and data privacy knowledge in two ways. First, by providing information on AI types (natural language processing, machine learning, and deep learning) and how/what customer data AI uses (e.g., segmentation and targeting, personalization, and customer service) along with a discussion of the accompanying arising data privacy issues. Then, this chapter will provide potential solutions to the problems presented and identified throughout this chapter (e.g., data value propositions, degree of personalization, and federated learning). The identified privacy issues and accompanying solutions within this chapter will hopefully aid the understanding of current and future marketing practitioners and academics in their use and understanding of AI.
One of my favorite topics for (heated) debate. (AI is only a tool?)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4220854
Untangling the Author/Inventor(Ship) Issues in the Artificial Intelligence-Intellectual Output
The growing sophistication and diffusion of Artificial Intelligence (AI) in creative tasks is triggering the assumptions that the AI machine (rather than human) should be considered as an author/inventor of the intellectual output produce by or with the help of AI techniques. Due to this paradigm shift, the orthodox conceptions of authorship and inventorship under intellectual property (IP) regime are being challenged in ways that have never been experienced before. Since the major area of existing literature on IP policy has not examined the technological machinery of AI system in depth, this study primarily investigates various technical concepts and aspects behind the working mechanism of an AI system. It provides a brief analysis of AI-human interaction in the production process of AI-intellectual output (AIIO) and points out that the human actor (designer, programmer, etc.) uses the AI system as a problem-solving tool to produce desired intellectual output. Furthermore, the study examines authorship and inventorship norms under current IP realm and posits that only human actor should be considered as author and inventor of the AIIO.
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