scholarly journals How to translate artificial intelligence? Myths and justifications in public discourse

2020 ◽  
Vol 7 (1) ◽  
pp. 205395172091996 ◽  
Author(s):  
Jonathan Roberge ◽  
Marius Senneville ◽  
Kevin Morin
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Science And Technology Studies ◽  
Public Discourse ◽  
Social Expectations ◽  
Specific Language ◽  
The Public ◽  
Gradual Introduction ◽  
Congressional Hearing ◽  
The Many

Automated technologies populating today’s online world rely on social expectations about how “smart” they appear to be. Algorithmic processing, as well as bias and missteps in the course of their development, all come to shape a cultural realm that in turn determines what they come to be about. It is our contention that a robust analytical frame could be derived from culturally driven Science and Technology Studies while focusing on Callon’s concept of translation. Excitement and apprehensions must find a specific language to move past a state of latency. Translations are thus contextual and highly performative, transforming justifications into legitimate claims, translators into discursive entrepreneurs, and power relations into new forms of governance and governmentality. In this piece, we discuss three cases in which artificial intelligence was deciphered to the public: (i) the Montreal Declaration for a Responsible Development of Artificial Intelligence, held as a prime example of how stakeholders manage to establish the terms of the debate on ethical artificial intelligence while avoiding substantive commitment; (ii) Mark Zuckerberg’s 2018 congressional hearing, where he construed machine learning as the solution to the many problems the platform might encounter; and (iii) the normative renegotiations surrounding the gradual introduction of “killer robots” in military engagements. Of interest are not only the rational arguments put forward, but also the rhetorical maneuvers deployed. Through the examination of the ramifications of these translations, we intend to show how they are constructed in face of and in relation to forms of criticisms, thus revealing the highly cybernetic deployment of artificial intelligence technologies.

scholarly journals Before and beyond trust: reliance in medical AI

2021 ◽  
pp. medethics-2020-107095
Author(s):  
Charalampia (Xaroula) Kerasidou ◽  
Angeliki Kerasidou ◽  
Monika Buscher ◽  
Stephen Wilkinson
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
New Technology ◽  
Public Trust ◽  
Learning Technologies ◽  
Data Driven ◽  
Policy Makers ◽  
The Public ◽  
Regulatory Frameworks ◽  
Practice Of Medicine

Artificial intelligence (AI) is changing healthcare and the practice of medicine as data-driven science and machine-learning technologies, in particular, are contributing to a variety of medical and clinical tasks. Such advancements have also raised many questions, especially about public trust. As a response to these concerns there has been a concentrated effort from public bodies, policy-makers and technology companies leading the way in AI to address what is identified as a "public trust deficit". This paper argues that a focus on trust as the basis upon which a relationship between this new technology and the public is built is, at best, ineffective, at worst, inappropriate or even dangerous, as it diverts attention from what is actually needed to actively warrant trust. Instead of agonising about how to facilitate trust, a type of relationship which can leave those trusting vulnerable and exposed, we argue that efforts should be focused on the difficult and dynamic process of ensuring reliance underwritten by strong legal and regulatory frameworks. From there, trust could emerge but not merely as a means to an end. Instead, as something to work in practice towards; that is, the deserved result of an ongoing ethical relationship where there is the appropriate, enforceable and reliable regulatory infrastructure in place for problems, challenges and power asymmetries to be continuously accounted for and appropriately redressed.

How Media Shapes the Public Discourse and Influences Health

2020 ◽  
pp. 23-35
Author(s):  
Alonzo L. Plough
Keyword(s):  
News Media ◽  
Public Discourse ◽  
Multiple Roles ◽  
Health Issues ◽  
The Public ◽  
Inaccurate Information ◽  
Modern Media ◽  
Multiple Media ◽  
American Society ◽  
The Many

This chapter describes the multiple roles of modern media in determining not only what consumers know, but also how and what they think. The exponential growth of ideologically driven cable channels and social media, dovetailing with cutbacks in newspaper staffing and coverage, point to the many ways that the power and reach of media are shifting even as they continue to reshape American society and norms. In this environment, multiple media compete for viewers, readers, and listeners who will click on their websites, buy their products, sign their petitions, and often accept their spin, especially if it reinforces personal perspectives. Thoughtful information about complex public health issues is easily lost in that context, leading too many people to base their decision-making on incomplete, biased, and even inaccurate information. For the news media to help build a Culture of Health, people need to understand how it works, what it does, and how it can be used for widespread benefit.

scholarly journals Public Opinions and Concerns Regarding the Canadian Prime Minister’s Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques

10.2196/23957 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e23957
Author(s):  
Chengda Zheng ◽  
Jia Xue ◽  
Yumin Sun ◽  
Tingshao Zhu
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Public Discourse ◽  
Latent Dirichlet Allocation ◽  
Prime Minister ◽  
Machine Learning Techniques ◽  
Future Health ◽  
The Public ◽  
Learning Techniques ◽  
The Government

Background During the COVID-19 pandemic in Canada, Prime Minister Justin Trudeau provided updates on the novel coronavirus and the government’s responses to the pandemic in his daily briefings from March 13 to May 22, 2020, delivered on the official Canadian Broadcasting Corporation (CBC) YouTube channel. Objective The aim of this study was to examine comments on Canadian Prime Minister Trudeau’s COVID-19 daily briefings by YouTube users and track these comments to extract the changing dynamics of the opinions and concerns of the public over time. Methods We used machine learning techniques to longitudinally analyze a total of 46,732 English YouTube comments that were retrieved from 57 videos of Prime Minister Trudeau’s COVID-19 daily briefings from March 13 to May 22, 2020. A natural language processing model, latent Dirichlet allocation, was used to choose salient topics among the sampled comments for each of the 57 videos. Thematic analysis was used to classify and summarize these salient topics into different prominent themes. Results We found 11 prominent themes, including strict border measures, public responses to Prime Minister Trudeau’s policies, essential work and frontline workers, individuals’ financial challenges, rental and mortgage subsidies, quarantine, government financial aid for enterprises and individuals, personal protective equipment, Canada and China’s relationship, vaccines, and reopening. Conclusions This study is the first to longitudinally investigate public discourse and concerns related to Prime Minister Trudeau’s daily COVID-19 briefings in Canada. This study contributes to establishing a real-time feedback loop between the public and public health officials on social media. Hearing and reacting to real concerns from the public can enhance trust between the government and the public to prepare for future health emergencies.

scholarly journals WHO'S CHOOSING THE NEWS; ARTIFICIAL INTELLIGENCE AND THEIR IMPLICATIONS FOR PUBLIC MEDIA DISCOURSE

2020 ◽  
Author(s):  
Sina Summers
Keyword(s):  
Artificial Intelligence ◽  
Public Discourse ◽  
Public Life ◽  
Media Discourse ◽  
The Public ◽  
Public Media ◽  
Level Of Understanding ◽  
Traditional Roles

This thesis inquiry investigates how algorithms operate generally to affect the dissemination of news information to audiences. This research aimed to find what the implications of AI used in these ways are for traditional roles played by media news in public life – such as informing the public in the public’s interests and enabling informed public discourse. This research asks also to what extent the use and effect of AI algorithms are transparent to audiences and how this level of understanding by audiences (or lack of understanding) affects the informing role of media.

scholarly journals Review on Existing Fire Monitoring and Extinguishing Systems In Various Domain Verticals

2021 ◽  
Vol 23 (3) ◽  
Author(s):  
Naina Mahile ◽  
◽  
Dipali Chakole ◽  
Nikita Kotangale ◽  
Mitali Charde ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Fire Safety ◽  
Public Awareness ◽  
Fire Control ◽  
Main Motivation ◽  
Fire Monitoring ◽  
The Public ◽  
Drastic Increase ◽  
Safety Systems

Fire is one of the most frequently occurring and destructive disasters and it is extremely serious hazard to people life safety. It is an undesirable mishap which emits heat, smoke or flame and gets converted in the huge fire. Over the last few years, the demand of fire safety systems has taken a drastic increase due to the public awareness. The main motivation of this paper is to review the existing fire monitoring and extinguishing systems in various verticals of the working domains. Also it gives the brief about the design of automatic sensor based fire alerts, and extinguishing system inferring the Artificial Intelligence and machine learning. The system will be able to locate the victim location and intimation to various stations to be included in the fire control the fire exposures. By implementing the proposed system in a particular area, it is possible to spot the fire within small course of time, and extinguish it without risking human lives.

Synthetic Biology between Self-Regulation and Public Discourse: Ethical Issues and the Many Roles of the Ethicist

2017 ◽  
Vol 26 (2) ◽  
pp. 246-256 ◽  
Author(s):  
GARDAR ARNASON
Keyword(s):  
Synthetic Biology ◽  
Public Discourse ◽  
Ethical Issues ◽  
Self Regulation ◽  
Moral Judgments ◽  
The Public ◽  
Biology I ◽  
Technical Issues ◽  
The Many

Abstract:This article discusses the roles of ethicists in the governance of synthetic biology. I am particularly concerned with the idea of self-regulation of bioscience and its relationship to public discourse about ethical issues in bioscience. I will look at the role of philosophical ethicists at different levels and loci, from the “embedded ethicist” in the laboratory or research project, to ethicists’ impact on policy and public discourse. In a democratic society, the development of governance frameworks for emerging technologies, such as synthetic biology, needs to be guided by a well-informed public discourse. In the case of synthetic biology, the public discourse has to go further than merely considering technical issues of biosafety and biosecurity, or risk management, to consider more philosophical issues concerning the meaning and value of “life” between the natural and the synthetic. I argue that ethicists have moral expertise to bring to the public arena, which consists not only in guiding the debate but also in evaluating arguments and moral positions and making normative judgments. When ethicists make normative claims or moral judgments, they must be transparent about their theoretical positions and basic moral standpoints.

scholarly journals ‘Ai Theory of Justice’: Using Rawlsian Approaches to Legislate Better on Machine Learning in Government

Amicus Curiae ◽  
2020 ◽  
Vol 1 (3) ◽  
pp. 338-360
Author(s):  
Jamie Grace ◽  
Roxanne Bamford
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
John Rawls ◽  
Data Analytics ◽  
The Public ◽  
Theory Of Justice ◽  
Big Data Technologies ◽  
Applications Of Machine Learning

Policymaking is increasingly being informed by ‘big data’ technologies of analytics, machine learning and artificial intelligence (AI). John Rawls used particular principles of reasoning in his 1971 book, A Theory of Justice, which might help explore known problems of data bias, unfairness, accountability and privacy, in relation to applications of machine learning and AI in government. This paper will investigate how the current assortment of UK governmental policy and regulatory developments around AI in the public sector could be said to meet, or not meet, these Rawlsian principles, and what we might do better by incorporating them when we respond legislatively to this ongoing challenge. This paper uses a case study of data analytics and machine-learning regulation as the central means of this exploration of Rawlsian thinking in relation to the redevelopment of algorithmic governance.

scholarly journals INTERDISCURSIVITY, INTERTEXTUALITY AND PRECEDENT TEXTS IN THE WEBSITE FORUM MEDIALECT

2020 ◽  
Vol 18 (1) ◽  
pp. 66-78
Author(s):  
Oksana CHERVENKO ◽  
Snezhan VELIKOVA
Keyword(s):  
Public Space ◽  
News Media ◽  
Public Discourse ◽  
The Internet ◽  
Language Usage ◽  
Communicative Behavior ◽  
Specific Language ◽  
The Public ◽  
Internet Media ◽  
Linguistic Behavior

is article analyzes the phenomena of interdiscursivity, intertextuality, precedent texts and their functions in the websites forum medialect, which could be described as an online space, where specific language usage related to internet communication is manifested. The main purpose is, firstly, to comment on these functions and, secondly, to analyze their relationship to participants’ linguistic behavior established around a specific news media in the public discourse. By presenting specific solutions, the article discusses the categories of intertextuality, interdiscursivity, precedent texts, and medialect. The illustrations for the analysis are taken from predominantly news-oriented online journalistic websites, and the article analyzes the speech behavior of the participants in the comment section medialect. Based on specific examples, the article draws conclusions about the role of the internet media in the use of the three phenomena and of the manifestations of the cooperative and masking functions performed by intertextuality, interdiscursivity and precedent texts included in the linguistic range of the commentators. The roles of the three categories in the formation of thecommunicative act and its outcome are commented in terms of topics that are sensitive for both journalists and the commentators of their articles. These are mainly topics that attract multiple comments due to their significance for a group of users or for the whole society, such as ethnic minorities, migration, corruption, political practices, political actors, etc. Furthermore, they manage to provoke the activity, dexterity, originality of the ones taking part in the communicative acts and thus to create favorable conditions to observe web specific linguistic practices; to track specific language usage and the communicative behavior of the addressers in the public space, observable in the internet media.

scholarly journals Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers

2021 ◽  
Vol 71 ◽  
Author(s):  
Baobao Zhang ◽  
Markus Anderljung ◽  
Lauren Kahn ◽  
Noemi Dreksler ◽  
Michael C. Horowitz ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
International Governance ◽  
The Public ◽  
Scientific Organizations ◽  
Safety Research ◽  
The Us ◽  
Military Applications ◽  
Governance Strategies ◽  
Technical Solutions

Machine learning (ML) and artificial intelligence (AI) researchers play an important role in the ethics and governance of AI, including through their work, advocacy, and choice of employment. Nevertheless, this influential group's attitudes are not well understood, undermining our ability to discern consensuses or disagreements between AI/ML researchers. To examine these researchers' views, we conducted a survey of those who published in two top AI/ML conferences (N = 524). We compare these results with those from a 2016 survey of AI/ML researchers (Grace et al., 2018) and a 2018 survey of the US public (Zhang & Dafoe, 2020). We find that AI/ML researchers place high levels of trust in international organizations and scientific organizations to shape the development and use of AI in the public interest; moderate trust in most Western tech companies; and low trust in national militaries, Chinese tech companies, and Facebook. While the respondents were overwhelmingly opposed to AI/ML researchers working on lethal autonomous weapons, they are less opposed to researchers working on other military applications of AI, particularly logistics algorithms. A strong majority of respondents think that AI safety research should be prioritized and that ML institutions should conduct pre-publication review to assess potential harms. Being closer to the technology itself, AI/ML researchers are well placed to highlight new risks and develop technical solutions, so this novel attempt to measure their attitudes has broad relevance. The findings should help to improve how researchers, private sector executives, and policymakers think about regulations, governance frameworks, guiding principles, and national and international governance strategies for AI. This article appears in the special track on AI & Society.

scholarly journals WHO'S CHOOSING THE NEWS; ARTIFICIAL INTELLIGENCE AND THEIR IMPLICATIONS FOR PUBLIC MEDIA DISCOURSE

2020 ◽  
Author(s):  
Sina Summers
Keyword(s):  
Artificial Intelligence ◽  
Public Discourse ◽  
Public Life ◽  
Media Discourse ◽  
The Public ◽  
Public Media ◽  
Level Of Understanding ◽  
Traditional Roles

This thesis inquiry investigates how algorithms operate generally to affect the dissemination of news information to audiences. This research aimed to find what the implications of AI used in these ways are for traditional roles played by media news in public life – such as informing the public in the public’s interests and enabling informed public discourse. This research asks also to what extent the use and effect of AI algorithms are transparent to audiences and how this level of understanding by audiences (or lack of understanding) affects the informing role of media.

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