Speakers
Description
Ever since humans have been able to speak, words have been a tool for conveying what is important to us, what values we hold and what opinions we stand for. At the intersection of technology and ethics, we use machine learning to decode moral principles expressed in the language we use. However, quantifying ethical or moral views in media e.g. newspaper articles, interviews and books remains difficult until today. Machine Learning algorithms and AI evolve fast, making it possible to examine and evaluate huge amounts of text for underlying patterns. There are also different rating instruments for moral perspectives such as the Moral Foundations Dictionary. We aim to merge the fields of computer science and philosophy in a very interdisciplinary team. The development of a machine-based learning algorithm allows us to understand the moral connotations and views in thousands of e.g. newspaper articles at a time. Our goal is to use this technology to extract moral stances from textual sources, thereby gaining deeper and more nuanced insights into the societal evolution of ethical perspectives. Talking about euthanasia or assisted suicide: even though both terms explain the same issue, the moral valuation is entirely different. By observing ethical shifts and the transformation of opinions, we try to extrapolate the trend for the future. Our software and analysis methods provide helpful insights for connotation research of texts also in other areas e.g. political, sociological or other research. We also aim to guide meaningful discussions, promote understanding, and foster a informed and morally conscious future – e.g. by telling which articles might be biased.
