Dr. Jaana Parviainen
jaana.parviainen (at) uta.fi
Dr. Lauri Lahikainen
lauri.lahikainen (at) uta.fi
Artificial intelligence (AI), algorithms, the Internet of Things (IoT) and machine learning raise serious considerations related to politics, democratic developments and economy regarding privacy, transparency, safety and the nature of work in societies all over the world. There are considerable uncertainties and risks about AI, including the delegation of decision-making to machines, increasing surveillance, lack of transparency on algorithms and whether technological solutions will overtake the development of governance and policy norms. One of the epistemological paradoxes related to data driven societies is that knowledge and non-knowing, information and disinformation, increase in equal amounts. For instance, online algorithms steering social media platforms make people vulnerable to disinformation since detailed ad tools let political campaigners exploit confirmation bias by tailoring messages to people who are already inclined to believe them. To explore and identify the threats of manufactured ignorance and spreading disinformation in AI-driven society, the proposed session suggests that the current development of information society must be analysed from the perspective of non-knowing, uncertainty, ignorance, unknown and unlearning.
We invite empirical, theoretical and methodological papers that address various aspects of AI-technologies related to issues of non-knowledge, ignorance and disinformation. While innovation brings opportunity from medicine to manufacturing, new technologies raise key questions and uncertainties for the future. How does the delegation of decision-making to machines change professionals’ work and their education systems? How do professionals and institutions handle the spread of disinformation and bullying generated by agents in social media and Internet? Regarding the transparency and accountability of data collection how do consumers and citizens can control and possess their personal data? Specifically, we welcome research papers that are related to discussions in ignorance studies, the philosophy of technology, social epistemology, the sociology of knowledge, media studies, science studies and feministic epistemology.