scholarly journals Viewpoint: Human-in-the-loop Artificial Intelligence

2019 ◽  
Vol 64 ◽  
pp. 243-252 ◽  
Author(s):  
Fabio Massimo Zanzotto
Keyword(s):  
Artificial Intelligence ◽  
Dark Side ◽  
Job Seekers ◽  
Job Market ◽  
Robin Hood ◽  
Human In The Loop ◽  
Intelligent Machines ◽  
Bright Future ◽  
Large Numbers ◽  
Unskilled Workers

Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future may have a possible dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers may need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustained by the biggest knowledge theft of the recent years. Many learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions. By passionately doing their jobs, many of these workers are shooting themselves in the feet. In this paper, we propose Human-in-the-loop Artificial Intelligence (HitAI) as a fairer paradigm for AI systems. Recognizing that any AI system has humans in the loop, HitAI will reward these aware and unaware knowledge producers with a different scheme: decisions of AI systems generating revenues will repay the legitimate owners of the knowledge used for taking those decisions. As modern Merry Men, HitAI researchers should fight for a fairer Robin Hood Artificial Intelligence that gives back what it steals. This article is part of the special track on AI and Society.

The Dark Side of Artificial Intelligence: Challenges for the Legal System

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
Willem Gravett
Keyword(s):  
Artificial Intelligence ◽  
Legal System ◽  
Indirect Effects ◽  
Current Trend ◽  
Dark Side ◽  
Work Practices ◽  
Direct And Indirect Effects ◽  
Autonomous Machines ◽  
State Surveillance

The development of artificial intelligence has the potential to transform lives and work practices, raise efficiency, savings and safety levels, and provide enhanced levels of services. However, the current trend towards developing smart and autonomous machines with the capacity to be trained and make decisions independently holds not only economic advantages, but also a variety of concerns regarding their direct and indirect effects on society as a whole. This article examines some of these concerns, specifically in the areas of privacy and autonomy, state surveillance, and bias and algorithmic transparency. It concludes with an analysis of the challenges that the legal system faces in regulating the burgeoning field of artificial intelligence.

AI Narratives

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Ancient Greece ◽  
Historical Overview ◽  
Intelligent Machines ◽  
Narrative History ◽  
History Of ◽  
Imaginative Thinking ◽  
The Relationship ◽  
Insight Into

This book is the first to examine the history of imaginative thinking about intelligent machines. As real artificial intelligence (AI) begins to touch on all aspects of our lives, this long narrative history shapes how the technology is developed, deployed, and regulated. It is therefore a crucial social and ethical issue. Part I of this book provides a historical overview from ancient Greece to the start of modernity. These chapters explore the revealing prehistory of key concerns of contemporary AI discourse, from the nature of mind and creativity to issues of power and rights, from the tension between fascination and ambivalence to investigations into artificial voices and technophobia. Part II focuses on the twentieth and twenty-first centuries in which a greater density of narratives emerged alongside rapid developments in AI technology. These chapters reveal not only how AI narratives have consistently been entangled with the emergence of real robotics and AI, but also how they offer a rich source of insight into how we might live with these revolutionary machines. Through their close textual engagements, these chapters explore the relationship between imaginative narratives and contemporary debates about AI’s social, ethical, and philosophical consequences, including questions of dehumanization, automation, anthropomorphization, cybernetics, cyberpunk, immortality, slavery, and governance. The contributions, from leading humanities and social science scholars, show that narratives about AI offer a crucial epistemic site for exploring contemporary debates about these powerful new technologies.

Mastering the Job Market

2021 ◽  
Author(s):  
Elizabeth L. Shoenfelt
Keyword(s):  
Job Search ◽  
Technical Writing ◽  
American Psychological Association ◽  
Oral Communication ◽  
Nationwide Survey ◽  
Job Seekers ◽  
Job Market ◽  
Master's Programs ◽  
Knowledge And Skills ◽  
Business Acumen

Mastering the Job Market: Career Issues for Master’s Level Industrial-Organizational Psychologists is the definitive source for practical advice and data-based recommendations addressing key issues leading to successful careers as industrial-organizational (I-O) master’s practitioners. Both the U.S. Bureau of Labor Statistics and the American Psychological Association have reported a bright outlook for I-O master’s graduates. The increased interest in and growth of I-O master’s programs and graduates are attributed to higher visibility in the workplace, readily obtained jobs, interesting work, and great pay. A large nationwide survey of I-O master’s practitioners and their employers lays the foundation for the data-based recommendations throughout the book. Authors from top-ranked I-O master’s programs address topics such as the job search, applying for jobs, on-boarding, organizational roles, salaries, career transitions, and maintaining professionalism throughout one’s career. Critical insights into the nuts and bolts of conducting a job search and other specific strategies are provided to enable job seekers to land one or multiple job offers within six months of graduation. Competencies identified as essential for success as an I-O practitioner include core I-O knowledge and skills, as well as enabling competencies such as oral communication, business acumen, consulting skills, project management, ethics, and technical writing. Mentoring is discussed, and three best practices are recommended for maximizing mentoring relationships. Recommendations are made for professional development opportunities for I-O master’s graduates to increase their knowledge and skills and to advance their careers. Graduates overwhelmingly perceive their I-O master’s degree to be valuable for their career success.

scholarly journals Artificial Intelligence (AI) and Its Associated Ethical Issues

ICR Journal ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 124-126
Author(s):  
Shahino Mah Abdulllah
Keyword(s):  
Artificial Intelligence ◽  
Real World ◽  
Ethical Issues ◽  
Economic Inequality ◽  
Human Behaviour ◽  
Intelligent Machines ◽  
Normal Shift

The adoption of AI in many industries has been regarded by some as a threat to low- and middle-skill workers, as it will drastically cut down reliance on the human workforce. Besides unemployment, there are also concerns about rising economic inequality caused by AI-driven companies. With fewer employees, these companies could gain a disproportionate advantage over conventional companies that still depend on normal, shift-based systems. There is also the issue that some AI bots have achieved the capability to interact with humans and build relationships through conversations. This influential communication could eventually enable these bots to affect human behaviour and possibly trigger certain actions. Significantly, therefore, such intelligent machines are not immune to mistakes and confusion since not all possible examples of real world interaction are covered during their training; this weakness could be manipulated to fulfil certain ends. Also, Al cannot be expected to be entirely fair and neutral, since it is dependent on human programmers, who have their own interests and whims.

scholarly journals Searching for employment: highly educated immigrant women and combined capabilities

2017 ◽  
Vol 10 (1) ◽  
pp. 35-42
Author(s):  
Tytti Steel ◽  
Marjut Jyrkinen
Keyword(s):  
Capability Approach ◽  
Immigrant Women ◽  
Research Question ◽  
Third Sector ◽  
Job Seekers ◽  
Job Market ◽  
Enabling Factors ◽  
Employment Services ◽  
Highly Educated ◽  
Gender And Age

Our paper addresses the ways in which highly educated immigrant women encounter and experience employment services in Finland. This qualitative study examines a group of women who have experience with both governmentally funded Employment and Economic Centre services (TE Services) and services offered by the third sector. The research question in this paper is as follows: How do the employment services support the capabilities of immigrant women job seekers trying to find work? Our analysis is inspired by Sen’s capability approach and Nussbaum’s concept of combined capabilities. The first empirical section addresses women with a foreign background as job seekers and their internal capabilities. We look at the enabling factors and hurdles faced by highly educated immigrant women trying to enter the job market due to their gender and age. In the second empirical section, we analyse how the combined capabilities are constructed through contacts with employment services.

scholarly journals Challenges of digitalization and artificial intelligence for modern economies, societies and management

2020 ◽  
Vol 28 (3) ◽  
pp. 556-567
Author(s):  
Rolf Clauberg
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Technical Information ◽  
Developed Countries ◽  
Negative Effects ◽  
Physical Systems ◽  
Large Numbers ◽  
Official Policy ◽  
The Usa ◽  
New Jobs

This study aims at identifying the challenges of digitalization and artificial intelligence for modern economies, societies and business administration. The implementation of digitalization schemes as Industry 4.0 are presently official policy of many developed countries. The goal is optimization of production processes and supply chains. Artificial intelligence is also affecting many fields. Both technologies are expected to substantially change working conditions for many people. It is important to identify the kind and impact of these changes and possible means to minimize negative effects. For this purpose, this study uses previous results about the disappearance of manufacturing jobs in the USA and their impact on different groups of society together with technical information about the new technologies to deduce expected changes caused by digitalization and artificial intelligence. Results are that both technologies will destroy large numbers of jobs and complete job classes while at the same time creating new jobs very different from the ones destroyed. Extensive permanent education and re-education of employees will be necessary to minimize negative effects, probably even changes to a more broad-based education to improve the potential of job changes into completely new fields. In addition, the technical information about digitalization in cyber-physical systems points to dangers that will require solutions on the international level.

scholarly journals El sesgo de la máquina en la toma de decisiones en el proceso penal.

2020 ◽  
Vol 6 (2) ◽  
pp. 54-71
Author(s):  
Raquel Borges Blázquez
Keyword(s):  
Artificial Intelligence ◽  
The Other ◽  
Human Being ◽  
Criminal Process ◽  
Ethical Problems ◽  
Intelligent Machines ◽  
Other Hand ◽  
Toma De Decisiones ◽  
Legal Thinking ◽  
The One

Artificial intelligence has countless advantages in our lives. On the one hand, computer’s capacity to store and connect data is far superior to human capacity. On the other hand, its “intelligence” also involves deep ethical problems that the law must respond to. I say “intelligence” because nowadays machines are not intelligent. Machines only use the data that a human being has previously offered as true. The truth is relative and the data will have the same biases and prejudices as the human who programs the machine. In other words, machines will be racist, sexist and classist if their programmers are. Furthermore, we are facing a new problem: the difficulty to understand the algorithm of those who apply the law.This situation forces us to rethink the criminal process, including artificial intelligence and spinning very thinly indicating how, when, why and under what assumptions we can make use of artificial intelligence and, above all, who is going to program it. At the end of the day, as Silvia Barona indicates, perhaps the question should be: who is going to control global legal thinking?

scholarly journals How the Brain might use Division

2020 ◽  
Vol 8 ◽  
pp. 126-137
Author(s):  
Kieran Greer
Keyword(s):  
Artificial Intelligence ◽  
Binary System ◽  
Problem Size ◽  
Symbol Manipulation ◽  
Mathematical Functions ◽  
Binary Operations ◽  
Neural Architecture ◽  
Large Numbers ◽  
The Brain

One of the most fundamental questions in Biology or Artificial Intelligence is how the human brainperforms mathematical functions. How does a neural architecture that may organise itself mostly throughstatistics, know what to do? One possibility is to extract the problem to something more abstract. This becomesclear when thinking about how the brain handles large numbers, for example to the power of something, whensimply summing to an answer is not feasible. In this paper, the author suggests that the maths question can beanswered more easily if the problem is changed into one of symbol manipulation and not just number counting.If symbols can be compared and manipulated, maybe without understanding completely what they are, then themathematical operations become relative and some of them might even be rote learned. The proposed systemmay also be suggested as an alternative to the traditional computer binary system. Any of the actual maths stillbreaks down into binary operations, while a more symbolic level above that can manipulate the numbers andreduce the problem size, thus making the binary operations simpler. An interesting result of looking at this is thepossibility of a new fractal equation resulting from division, that can be used as a measure of good fit and wouldhelp the brain decide how to solve something through self-replacement and a comparison with this good fit.

A Behavioral Economics Approach to Digitalization

2019 ◽  
pp. 107-122
Author(s):  
Dirk Beerbaum ◽  
Julia Margarete Puaschunder
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Social Media ◽  
Behavioral Economics ◽  
Field Research ◽  
Learning Systems ◽  
Business Reporting ◽  
Intelligent Machines ◽  
Private Investors ◽  
Coding Rules

Technological improvement in the age of information has increased the possibilities to control the innocent social media users or penalize private investors and reap the benefits of their existence in hidden persuasion and discrimination. This chapter takes as a case the transparency technology XBRL (eXtensible Business Reporting Language), which should make data more accessible as well as usable for private investors. Considering theoretical literature and field research, a representation issue for principles-based accounting taxonomies exists, which intelligent machines applying artificial intelligence (AI) nudge to facilitate decision usefulness. This chapter conceptualizes ethical questions arising from the taxonomy engineering based on machine learning systems and advocates for a democratization of information, education, and transparency about nudges and coding rules.

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