The Opinions for the Development of AI in Turkey
English Translation is sooonish 🙂
The Opinions for the Development of AI in Turkey
English Translation is sooonish 🙂
Artificial Intelligence Assets and Criminal Law
“With the development of technology, artificial intelligence assets have started to be used in almost every area of our daily lives. It is anticipated that these assets, which are now available to people service and make their jobs easier, will achieve human status and do some professions in the future. These developments also bring some legal and criminal questions. What are the legal status of artificial intelligence assets, who will have criminal responsibility for crimes that arise due to their use, and what is their role in criminal proceedings are among the questions to be answered. The purpose of this study is to make an assessment on these questions with existing legal regulations. The methodology of the study is carried out as a literature review. As a result of the study, it has been concluded that artificial intelligence assets are in the status of ‘property’, cannot be held responsible for crimes due to their use, and cannot be replaced by the subjects (judges, prosecutors, lawyers) of the proceedings, although they have important contributions to the criminal proceedings. In this context, existing legal regulations are sufficient to solve the problems that will arise. However, if artificial intelligence assets acquire ‘human’ status as a fully autonomous and conscious entity, radical changes will be required in our legal system.”
can find original paper from the link below:
Is Turkish Copyright Law Ready to Protect Works Generated by
Dr. Hasan Kadir YILMAZTEKİN
Türkiye Adalet Akademisi
GSÜHFD, 2020; 2: 1513-1586
Portreit generated via AI by Mario Klingemann
“Artificial intelligence (“AI”) nowadays immensely and importantly infiltrates our lives. From Apple’s Siri to Tesla’s auto-driving car and Amazon’s Alexa, we live in a world of AI goods.
The advent of AI-powered technologies increasingly affects people‟s life across the globe. With its technological advances, AI also shapes our economy and welfare.
Current AI Technologies can produce many works that might be subject of copyright law. An AI device’s ability to generate works raises the question of who will own the intellectual property rights over those works. Will it be the author who hires or contracts with the AI device programmer? Will it be the programmer? Or will it be the AI device itself? Or will it be a joint work?
In this article, we seek answers to these questions under European Union (EU), United States of America (US), United Kingdom (UK) laws and more comprehensively under Turkish law. In short, this study makes policy proposals for Turkish copyright law. It particularly offers a proposal of a solution based on a three-step test to single out the human authors(s) from the relevant actors around the AI device and model legal norms for AI-generated works.“
You can reach original article from the link below:
Feasibility Study on AI
Council of Europe
Ad Hoc Committee on AI
“As noted in various Council of Europe documents, including reports recently adopted by the Parliamentary Assembly (PACE), AI systems are substantially transforming individual lives and have a profound impact on the fabric of society and the functioning of its institutions. Their use has the capacity to generate substantive benefits in numerous domains, such as healthcare, transport, education and public administration, generating promising opportunities for humanity at large. At the same time, the development and use of AI systems also entails substantial risks, in particular in relation to interference with human rights, democracy and the rule of law, the core elements upon which our European societies are built.
AI systems should be seen as “socio-technical systems”, in the sense that the impact of an AI system – whatever its underlying technology – depends not only on the system’s design, but also on the way in which the system is developed and used within a broader environment, including the data used, its intended purpose, functionality and accuracy, the scale of deployment, and the broader organisational, societal and legal context in which it is used. The positive or negative consequences of AI systems depend also on the values and behaviour of the human beings that develop and deploy them, which leads to the importance of ensuring human responsibility. There are, however, some distinct characteristics of AI systems that set them apart from other technologies in relation to both their positive and negative impact on human rights, democracy and the rule of law.
First, the scale, connectedness and reach of AI systems can amplify certain risks that are also inherent in other technologies or human behaviour. AI systems can analyse an unprecedented amount of fine-grained data (including highly sensitive personal data) at a much faster pace than humans. This ability can lead AI systems to be used in a way that perpetuates or amplifies unjust bias, also based on new discrimination grounds in case of so called “proxy discrimination”. The increased prominence of proxy discrimination in the context of machine learning may raise interpretive questions about the distinction between direct and indirect discrimination or, indeed, the adequacy of this distinction as it is traditionally understood. Moreover, AI systems are subject to statistical error rates. Even if the error rate of a system applied to millions of people is close to zero, thousands of people can still be adversely impacted due to the scale of deployment and interconnectivity of the systems. On the other side, the scale and reach of AI systems also imply that they can be used to mitigate certain risks and biases that are also inherent in other technologies or human behaviour, and to monitor and reduce human error rates.
Second, the complexity or opacity of many AI systems (in particular in the case of machine learning applications) can make it difficult for humans, including system developers, to understand or trace the system’s functioning or outcome. This opacity, in combination with the involvement of many different actors at different stages during the system’s lifecycle, further complicates the identification of the agent(s) responsible for a potential negative outcome, hence reducing human responsibility and accountability.
Third, certain AI systems can re-calibrate themselves through feedback and reinforcement learning. However, if an AI system is re-trained on data resulting from its own decisions which contains unjust biases, errors, inaccuracies or other deficiencies, a vicious feedback loop may arise which can lead to a discriminatory, erroneous or malicious functioning of the system and which can be difficult to detect.”
You can reach original study from the link below:
Sociological Imagination: Artificial Intelligence and Alan Turing
DTCF Press, 2017
“C. Wright Mills views sociological imagination as the ability to relate the most intimate to the most impersonal. There are essential linkages between personal troubles and social issues. The sociologist should be able to trace the linkages between biographies and histories. Sociological imagination necessitates sensibility, commitment and responsibility since sociology is a practice of life as well as a practice of work. Sociology is, then, a practice that potentially everyone can perform. The crucial condition is the existence of sociological imagination and sensibility. This sensibility indicates the capacity to picture a social imaginary, however broad or limited. This paper traces the sociological imagination of Alan Turing, who is often considered as the founder of modern computing technology. The history of Turing’s scientific endeavours follows (and is followed by) his biography, revealing the strong linkages between his life and work. Turing’s sensible, committed and responsible attitude is clear in several cases. This paper focuses on the case of artificial intelligence in order to assess Turing’s sociological imagination. The paper claims that Alan Turing has the sensibility and imagination to picture a social imaginary. In order to analyse Turing’s imagination in the example of artificial intelligence, the paper refers to three faces of sociological imagination of Mills: (1) emphasis on the relation between the most intimate and the most impersonal; (2)
developing new sensibilities and new spaces of sensibility; (3) imagining a social picture. By referring to these three faces, the paper analyses the biography of Turing, his mathematical but also sociological imagination, and artificial intelligence as the product of this imagination; and again through artificial intelligence, it further aims to demonstrate the different possibilities in C. W. Mills’ concept of sociological imagination.”
You can find original and full article from the link below:
Towards Regulation of AI Systems
The CAHAI Secretariat
Title 1. International Perspective
Preliminary Chapter introduces the present report, submitted by the CAHAI to the Committee of Ministers and details the progress achieved to date, taking into account the impact of COVID-19 pandemic measures. It also includes reflections on working methods, synergy and complementarity with other relevant stakeholders and proposals for further action by the CAHAI by means of a robust and clear roadmap.
Chapter 1 outlines the impact of AI on human rights, democracy and rule of law. It identifies those human rights, as set out by the European Convention on Human Rights (“ECHR”), its Protocols and the European Social Charter (“ESC”), that are currently most impacted or likely to be impacted by AI.
Chapter 2 maps the relevant corpus of soft law documents and other ethical-legal frameworks developed by governmental and non- governmental organisations globally with a twofold aim. First, we want to monitor this ever-evolving spectrum of non-mandatory governance instruments. Second, we want to prospectively assess the impact of AI on ethical principles, human rights, the rule of law and democracy.
Chapter 3 aims to contribute to the drafting of future AI regulation by building on the existing binding instruments, contextualising their principles and providing key regulatory guidelines for a future legal framework, with a view to preserving the harmonisation of the existing legal framework in the field of human rights, democracy and the rule of law.
You can find original document from the link below:
Data Privacy Guidelines for AI Solutions
(All submissions must have been received by 2 November 2020.)
You can find original draft Guidelines from the link below:
Fifty Cognitive Biases in the Modern World
English translation is sooonish 🙂
Preventing Discrimination Caused by the Use of Artificial Intelligence
Committee on Equality and Non-Discrimination
Rapporteur: Christophe LACROIX, Belgium, 2020
Artificial intelligence (AI), by allowing massive upscaling of automated decision-making processes, creates opportunities for efficiency gains – but in parallel, it can perpetuate and exacerbate discrimination. Public and private sector uses of AI have already been shown to have a discriminatory impact, while information flows tend to highlight extremes and foster hate. The use of biased datasets, design that fails to integrate the need to protect human rights, the lack of transparency of algorithms and of accountability for their impact, as well as a lack of diversity in AI teams, all contribute to this phenomenon.
States must act now to prevent AI from having a discriminatory impact in our societies, and should work together to develop international standards in this field.
Parliaments must moreover play an active role in overseeing the use of AI-based technologies and ensuring it is subject to public scrutiny. Domestic antidiscrimination legislation should be reviewed and amended to ensure that victims of discrimination caused by the use of AI have access to an effective remedy, and national equality bodies should be effectively equipped to deal with the impact of AI-based technologies.
Respect for equality and non-discrimination must be integrated from the outset in the design of AI-based systems, and tested before their deployment. The public and private sectors should actively promote diversity and interdisciplinary approaches in technology studies and professions.
You can reach original report from the link below:
A Framework for Developing a National Artificial Intelligence Strategy
World Economic Forum
Over the past decade, artificial intelligence (AI) has emerged as the software engine that drives the Fourth Industrial Revolution, a technological force affecting all disciplines, economies and industries. The exponential growth in computing infrastructure combined with the dramatic reduction in the cost of obtaining, processing, storing and transmitting data has revolutionized the way software is developed, and automation is carried out. Put simply, we have moved from machine programming to machine learning. This transformation has created great opportunities but poses serious risks. Various stakeholders, including governments, corporations, academics and civil society organizations have been making efforts to exploit the benefits it provides and to prepare for the risks it poses. Because government is responsible for protecting citizens from various harms and providing for collective goods and services, it has a unique duty to ensure that the ongoing Fourth Industrial Revolution creates benefits for the many, rather than the few.
To this end, various governments have embarked on the path to formulate and/or implement a national strategy for AI, starting with Canada in 2017. Such efforts are usually supported by multimillion-dollar – and, in a few cases, billion-dollar-plus – investments by national governments. Many more should follow given the appropriate guidance. This white paper is a modest effort to guide governments in their development of a national strategy for AI. As a rapidly developing technology, AI will have an impact on how enterprises produce, how consumers consume and how governments deliver services to citizens. AI also raises unprecedented challenges for governments in relation to algorithmic accountability, data protection, explainability of decision-making by machine-learning models and potential job displacements. These challenges require a new approach to understanding how AI and related technology developments can be used to achieve national goals and how their associated risks can be minimized. As AI will be used in all sectors of society and as it directly affects all citizens and all of the services provided by governments, it behoves governments to think carefully about how they create AI economies within their countries and how they can employ AI to solve problems as diverse as sustainability of ecosystems to healthcare. Each country will need AI for different things; for example, countries with ageing populations may not be so worried about jobs lost due to AI automation, whereas countries with youthful populations need to think of ways in which those young people can participate in the AI economy. Either way, this white paper provides a framework for national governments to follow while formulating a strategy of national preparedness and planning to draw benefits from AI developments.
The framework is the result of a holistic study of the various strategies and national plans prepared by various countries, including Canada, the United Kingdom, the United States, India, France, Singapore, Germany and the UAE. Additionally, the World Economic Forum team interviewed government employees responsible for developing their national AI strategies in order to gain a detailed understanding of the design process they followed. The authors analysed these strategies and designed processes to distil their best elements.
The framework aims to guide governments that are yet to develop a national strategy for AI or which are in the process of developing such a strategy. The framework will help the teams responsible for developing the national strategy to ask the right questions, follow the best practices, identify and involve the right stakeholders in the process and create the right set of outcome indicators. Essentially, the framework provides a way to create a “minimum viable” AI strategy for a nation.
You can find original report from the link below: