Setting the AI Code of Conduct for Turkey
Everyone Is Talking About AI — But Do They Mean the Same Thing?
Artificial Intelligence (AI) refers to machines that perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. AI is a general-purpose technology with applications in many different fields, and probably like electricity –another general-purpose technology– will have a transformative impact on societies. Governments are in the process of adopting “national AI strategies” to seize the opportunities and respond to the challenges brought by the AI technology. Just like the 21 pioneer economies that adopted or are in the process of adopting AI strategies, Turkey urgently needs to start a discussion around its own AI strategy, which might consists of many interlinked perspectives. However, this working paper approaches Turkey’s AI strategy challenge from only one perspective: AI ethics.
AI is an umbrella term for a set of different technologies developed in the last 70 years. While general AI refers to a system that performs a full range of human cognitive tasks, most daily deliberations on AI, including this proposal, refer to narrow AI, which focuses on single particular tasks such as speech and image recognition, natural language processing, targeted advertising, and autonomous lethal weapons.
Most AI applications today are based on a concept called “Big Data Analytics”. Big data can be thought of as an asset that is difficult to exploit. AI can be seen as a key to unlocking the value of big data; and machine learning is one of the technical mechanisms that underpins and facilitates AI. The combination of all three concepts can be called big data analytics. Some of the distinctive aspects of big data analytics are:
- The use of algorithms,
- The opacity of the processing,
- The tendency to collect ‘all the data’,
- The repurposing of data, and
- The use of new types of data.
- Countless empirical studies reveal that moral choices are not universal; there are harsh variations in global ethics. What is the risk that AI algorithms or data used to train them contain biases, which may detrimentally affect certain parts of Turkish society?
- How will pre-existing human power and rent-generating structures impact algorithmic effects? To what extent should we look for transparency in algorithms used by the government in the public sphere or by businesses, including global AI companies?
- How much regulatory localization should there be at the expense of synchronization?
- Many technological catastrophes have revealed that it is less costly to prevent than fix. What are the preemptive measures to be taken in order to minimize the effects of AI-resultant societal and/or ethical dilemmas?
- How can we ensure an AI-society that enables human self-realization, enhances human agency, increases societal capabilities and cultivates social cohesion?
- How might Turkey establish its own “AI code of conduct”? Should it even establish one, at all?
- AIWS REPORT ABOUT AI ETHICS; Michael Dukakis, Nguyen Anh Tuan, Thomas Patterson, Thomas Creely, Nazli Choucri, Paul Nemitz, Derek Reveron, Hiroshi Ishiguro, Eliot Weinman, Kazuo Yano, Boston, December 3, 2018, https://dukakis.bostonglobalforum.org/wp-content/uploads/sites/15/AIWS-Report-official-version-December-3.pdf
- An Overview of National AI Strategies by AI+Politics lists the following countries as published or working on a national AI strategy: Australia, Canada, China, Denmark, EU, Finland, France, Germany, India, Italy, Japan, Kenya, Malaysia, Mexico, New Zealand, Poland, Russia, Singapore, South Korea, Sweden, Taiwan, Tunisia, UAE, United Kingdom, United States. (https://medium.com/politics-ai/an-overview-of-national-ai-strategies-2a70ec6edfd)
- Purtova, Nadezhda, The Law of Everything. Broad Concept of Personal Data and Future of EU Data Protection Law (September 9, 2017). 2018 Law, Innovation and Technology 10(1). Available at SSRN: https://ssrn.com/abstract=3036355 or http://dx.doi.org/10.2139/ssrn.3036355
- Benkler, Yochai, et al. “Understanding Media and Information Quality in an Age of Artificial Intelligence, Automation...” Medium, 9 July 2018, com/berkman-klein-center/understanding-media-and-information-quality-in-an-age-of-artificial-intelligence-automation-a562620c7039.
- Paul Nemitz, Constitutional democracy and technology in the age of artificial intelligence. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, http://doi.org/10.1098/rsta.2018.0089.
- Tufekci, Zeynep. “How Social Media Took Us from Tahrir Square to Donald Trump.” MIT Technology Review, 15 Aug. 2018, technologyreview.com/s/611806/how-social-media-took-us-from-tahrir-square-to-donald-trump/.
- See, for instance, “Self-driving car dilemmas reveal that moral choices are not universal” by Amy Maxmen: https://www.nature.com/articles/d41586-018-07135-0
- Helbing, Dirk, The Automation of Society is Next: How to Survive the Digital Revolution (November, 2015). Available at SSRN: https://ssrn.com/abstract=2694312 or http://dx.doi.org/10.2139/ssrn.2694312
- Kahn, Peter H. and Batya Friedman. “Children's Moral and Ecological Reasoning about the Prince William Sound Oil Spill.” ERIC - Institute of Education Sciences, June 1995, eric.ed.gov/fulltext/ED390541.pdf.
- Eczacıbaşı Faruk, and Zeynep Tüfekçi. “Daha Yeni Başlıyor: Geleceğin Dünyasında Esneklik, Yakınsama, Ağ Yapısı ve Karanlık Taraf. Koç Üniversitesi, 2018, pp. 13.
- See, for instance, “IEEE-SA - The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems.” IEEE-SA - The IEEE Standards Association - Home, Dec. 2016, ieee.org/develop/indconn/ec/autonomous_systems.html.
- Klaus Schwab, “The Power of Dialogue in a Disrupted World”, https://www.project-syndicate.org/commentary/dialogue-for-policymaking-in-a-disrupted-world-by-klaus-schwab-2018-02