Robots and refugees: the human rights impacts of artificial intelligence and automated decision-making in migration

2021 ◽  
pp. 134-151
Author(s):  
Petra Molnar
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Human Rights ◽  
Automated Decision Making

scholarly journals Territorial and Digital Borders and Migrant Vulnerability Under a Pandemic Crisis

2021 ◽  
pp. 45-64
Author(s):  
Petra Molnar
Keyword(s):  
Decision Making ◽  
Human Rights ◽  
Big Data ◽  
Private Sector ◽  
Guinea Pigs ◽  
Technological Development ◽  
Forced Migration ◽  
Population Movements ◽  
Humanitarian Crises ◽  
Automated Decision Making

AbstractPeople on the move are often left out of conversations around technological development and become guinea pigs for testing new surveillance tools before bringing them to the wider population. These experiments range from big data predictions about population movements in humanitarian crises to automated decision-making in immigration and refugee applications to AI lie detectors at European airports. The Covid-19 pandemic has seen an increase of technological solutions presented as viable ways to stop its spread. Governments’ move toward biosurveillance has increased tracking, automated drones, and other technologies that purport to manage migration. However, refugees and people crossing borders are disproportionately targeted, with far-reaching impacts on various human rights. Drawing on interviews with affected communities in Belgium and Greece in 2020, this chapter explores how technological experiments on refugees are often discriminatory, breach privacy, and endanger lives. Lack of regulation of such technological experimentation and a pre-existing opaque decision-making ecosystem creates a governance gap that leaves room for far-reaching human rights impacts in this time of exception, with private sector interest setting the agenda. Blanket technological solutions do not address the root causes of displacement, forced migration, and economic inequality – all factors exacerbating the vulnerabilities communities on the move face in these pandemic times.

Blockchain-Enabled Internet of Things for Unsupervised Structural Health Monitoring in Potential Building Structures

2021 ◽  
pp. 158-170
Author(s):  
Wael Mohammad Alenazy
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Structural Health Monitoring ◽  
Internet Of Things ◽  
Health Monitoring ◽  
Remote Monitoring ◽  
Building Structures ◽  
Stress Strain ◽  
Structural Health ◽  
Automated Decision Making

The integration of internet of things, artificial intelligence, and blockchain enabled the monitoring of structural health with unattended and automated means. Remote monitoring mandates intelligent automated decision-making capability, which is still absent in present solutions. The proposed solution in this chapter contemplates the architecture of smart sensors, customized for individual structures, to regulate the monitoring of structural health through stress, strain, and bolted joints looseness. Long range sensors are deployed for transmitting the messages a longer distance than existing techniques. From the simulated results, different sensors record the monitoring information and transmit to the blockchain platform in terms of pressure points, temperature, pre-tension force, and the architecture deems the criticality of transactions. Blockchain platform will also be responsible for storage and accessibility of information from a decentralized medium, automation, and security.

scholarly journals In AI we trust? Perceptions about automated decision-making by artificial intelligence

AI & Society ◽  
2020 ◽  
Vol 35 (3) ◽  
pp. 611-623 ◽  
Author(s):  
Theo Araujo ◽  
Natali Helberger ◽  
Sanne Kruikemeier ◽  
Claes H. de Vreese
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Automated Decision Making

scholarly journals Strengthening legal protection against discrimination by algorithms and artificial intelligence

2020 ◽  
Author(s):  
Frederik Zuiderveen Borgesius
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Human Rights ◽  
Data Protection ◽  
Legal Protection ◽  
Indirect Discrimination ◽  
General Rules ◽  
Data Protection Law ◽  
The Right

Algorithmic decision-making and other types of artificial intelligence (AI) can be used to predict who will commit crime, who will be a good employee, who will default on a loan, etc. However, algorithmic decision-making can also threaten human rights, such as the right to non-discrimination. The paper evaluates current legal protection in Europe against discriminatory algorithmic decisions. The paper shows that non-discrimination law, in particular through the concept of indirect discrimination, prohibits many types of algorithmic discrimination. Data protection law could also help to defend people against discrimination. Proper enforcement of non-discrimination law and data protection law could help to protect people. However, the paper shows that both legal instruments have severe weaknesses when applied to artificial intelligence. The paper suggests how enforcement of current rules can be improved. The paper also explores whether additional rules are needed. The paper argues for sector-specific – rather than general – rules, and outlines an approach to regulate algorithmic decision-making.

scholarly journals Algorytm jako informacja publiczna w prawie europejskim

2021 ◽  
Author(s):  
Joanna Mazur
Keyword(s):  
Decision Making ◽  
European Union ◽  
Human Rights ◽  
European Law ◽  
The European Union ◽  
Court Of Justice ◽  
European Court ◽  
Access Information ◽  
The Right ◽  
Automated Decision Making

The author verifies the hypothesis concerning the possibility of using algorithms – applied in automated decision making in public sector – as information which is subject to the law governing the right to access information or the right to access official documents in European law. She discusses problems caused by the approach to these laws in the European Union, as well as lack of conformity of the jurisprudence between the Court of Justice of the European Union and the European Court of Human Rights.

Can public access to documents support the transparency of automated decision-making? The European Union law perspective

2020 ◽  
Author(s):  
Joanna Mazur
Keyword(s):  
Decision Making ◽  
European Union ◽  
Human Rights ◽  
Eu Law ◽  
The European Union ◽  
European Union Law ◽  
Access Information ◽  
The Right ◽  
Automated Decision Making ◽  
The Impact

ABSTRACT Due to the concerns which are raised regarding the impact of automated decision-making (ADM) on transparency and their potential discriminatory character, it is worth examining the possibility of applying legal measures which could serve to increase transparency of ADM systems. The article explores the possibility to consider algorithms used in ADM systems as documents subjected to the right to access documents in European Union (EU) law. It is focused on contrasting and comparing the approach based on the right to access public documents developed by the Court of Justice of European Union (CJEU) with the approach to the right to access public information as interpreted by the European Court of Human Rights (ECtHR). The analysis shows discrepancies in the perspectives presented by these Courts which result in a limited scope of the right to access public documents in EU law. Pointing out these differences may provide a motivation to clarify the meaning of the right to access information in EU law, the CJEU’s approach remaining as for now incoherent. The article presents the arguments for and ways of bringing together the approaches of the CJEU and the ECtHR in the light of a decreasing level of transparency resulting from the use of ADM in the public sector. It shows that in order to ensure compliance with EU law, it is necessary to rethink the role which the right to access information plays in the human rights catalogue.

Artificial intelligence for production engineering: a historical approach

Robotica ◽  
1987 ◽  
Vol 5 (2) ◽  
pp. 99-110 ◽  
Author(s):  
Igor Aleksander
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Visual Information ◽  
Design Stage ◽  
Production Engineering ◽  
Television Camera ◽  
Knowledge Based ◽  
Work Cycle ◽  
Programming Techniques ◽  
Automated Decision Making

SUMMARYThis paper describes the principles of the advanced programming techniques often dubbed Artificial Intelligence involved in decision making as may be of some value in matters related to production engineering. Automated decision making in the context of production can adopt many aspects. At the most obvious level, a robot may have to plan a sequence of actions on the basis of signals obtained from changing conditions in its environment. These signals may, indeed, be quite complex, for example the input of visual information from a television camera.At another level, automated planning may be required to schedule the entire work cycle of a plant that includes many robots as well as other types of automated machinery. The often-quoted dark factory is an example of this, where not only some of the operations (such as welding) are done by robots, but also the transport of part-completed assemblies is automatically scheduled as a set of actions for autonomic transporters and cranes. It is common practice for this activity to be preprogrammed to the greatest detail. Automated decision making is aimed at adding flexibility to the process so that it can absolve the system designer from having to forsee every eventuality at the design stage.Frequent reference is made in this context to artificial intelligence (AI), knowledge-based and expert systems. Although these topics are more readily associated with computer science, it is the automated factory, in general, and the robot, in particular, that will benefit from success in these fields. In this part of the paper we try to sharpen up this perspective, while in part II we aim to discuss the history of artificial intelligence in this context. In part III we discuss the industrial prospects for the field.

scholarly journals Integration of Artificial Intelligence into Dempster Shafer Theory: A Review on Decision Making in Condition Monitoring

2015 ◽  
Vol 773-774 ◽  
pp. 154-157 ◽  
Author(s):  
Muhammad Firdaus Rosli ◽  
Lim Meng Hee ◽  
M. Salman Leong
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Condition Monitoring ◽  
Support Vector ◽  
Dempster Shafer Theory ◽  
Basic Probability ◽  
Human Interpretation ◽  
The Individual ◽  
Shafer Theory ◽  
Automated Decision Making

Machines are the heart of most industries. By ensuring the health of machines, one could easily increase the company revenue and eliminates any safety threat related to machinery catastrophic failures. In condition monitoring (CM), questions often arise during decision making time whether the machine is still safe to run or not? Traditional CM approach depends heavily on human interpretation of results whereby decision is made solely based on the individual experience and knowledge about the machines. The advent of artificial intelligence (AI) and automated ways for decision making in CM provides a more objective and unbiased approach for CM industry and has become a topic of interest in the recent years. This paper reviews the techniques used for automated decision making in CM with emphasis given on Dempster-Shafer (D-S) evident theory and other basic probability assignment (BPA) techniques such as support vector machine (SVM) and etc.

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