Author: Yanmin Xu, Yitao Tao, Chunjiong Zhang, Mingxing Xie, Wengang Li, Jianjiang Tai; Publisher: Hindawi; Publication Year: 2022. The following article talks about how ethical considerations also need to be taken when using data for use of digital economies. This article discusses how digital economies are being introduced in parts of China, and what ethical issues can arise…
Author: Thomas Macaulay, Alejandro Saucedo; Publisher: The Next Web; Publication Year: 2022. The following article discusses how almost all artificial intelligence (AI) algorithms are inherently biased as they do exactly what us the programmers tell them to do and we are all inherently biased ourselves. This resource is an interview with Alejandro Saucedo, Chief Scientist at The Institute for Ethical AI, who discusses his main points of what needs to be…
Author: Mainak Mazumdar; Publisher: TED; Publication Year: N/A. In the following talk, Mainak argues that the biased data is what makes unethical artificial intelligence (AI), not the algorithms. Instead of spending time and money on enhancing algorithms, focus should be on obtaining unbiased data that makes ethical AI possible. He proposes 3 areas of improvement for this to happen: 1). Data infrastructure, 2)…
Author: Jennifer Buonantony; Publisher: Globe Newswire; Publication Year: 2022. The following article discusses how as the world moves to be more ethically minded and conscious about the spread of data, companies are even moving to capitalize on the trend, showing that it is not just the right thing to be ethical but also profitable. Camden is a newly launched platform to give users fine-tuned control over how their data is shared…
Author: James Kobielus; Publisher: Transforming Data with Intelligence (TDWI); Publication Year: 2021. The following article focuses on why there are ethical boundaries needed when building robotic assistants in this article. Developers of the artificial intelligence (AI) for these scenarios must build and train their creations to always operate in alignment with the intentions and interests of the responsible parties. To verify human accountability, there…
Author: James Arvanitakis, Andrew Francis, Oliver Obst; Publisher: The Conversation; Publication Year: 2018. The following article discusses how, as analysts, the main 2 ethical questions that are being asked are 1). What data should be collected and 2). How should the data be used? However, we should also ask and see who gets to make the decision in the first place. As it stands right now, the people who hold all the power to make the decision in how we use…
Author: Geoffrey Holtzman, Neda Khoshkhoo, Elaine Nsoesie; Publisher: The American Journal of Bioethics; Publication Year: 2022. The following article discusses how there is a consistent racial disparity in data, particularly as this article points out, in the health care industry. More specifically races and ethnicities which are experiencing a data gap are also typically at higher risk for health problems. The main issue to address here is that there is a misrepresentation in the data…
Author: Trey Bradley et. al.; Publisher: Federal Data Strategy; Publication Year: 2019. The following resource is considered a data ethics framework for the federal government. Some key players in the data ethics decision making field of the government helped contribute to this paper and are listed with their department on the development team page. While for the most part this is only broad guidelines it is important to know what…
Author: Danielle Clifford; Publisher: Pinsent Masons; Publication Year: 2021. The following article discusses how the data ethics challenge spans multiple vectors. One of the most concerning issues centers around the artificial intelligence (AI) and machine learning-powered algorithms that form a key part of many organizations’ operations. These technologies have the potential to revolutionize crucial sectors such as…
Author: Danel Goddemeyer, Dominikus Baur; Publisher: TEDx; Publication Year: N/A. The following TED Talk features a collaborative audience demonstration on collecting data. It makes connections to how easy is it to leave a data trail and how much these algorithms are like magic tricks as we can’t see what’s going on behind the scenes…