Artificial Intelligence (AI) is one of the most transformative technologies of our time, with the potential to revolutionize various industries and improve our lives in countless ways.
However, as we continue to develop and implement AI, it is crucial to examine its potential impact on society, including its potential to perpetuate racial biases and discrimination. While AI is often seen as a neutral technology, it is only as unbiased as the data and algorithms used to train and develop it.
As the world nears a crucial turning point regarding artificial intelligence becoming part of normal life, specialists must thoroughly examine the “racial specters” implanted within the technology.
The 9th Annual Lecture from the Edmund W. Gordon Institute for Urban and Minority Education was co-hosted by TC’s Ezekiel Dixon-Román, who gave this year’s Annual Sachs Lecture.
Professor Dixon-Román, the Director of the Gordon Institute and a Professor of Critical Race, Media, and Educational Studies, elucidated.
Professor Dixon-Román says:
“Computational methods have the potential to radically change public policy, human and educational services and city governance.”
“Yet, cybernetic systems do have sociopolitical implications. Although these automated systems of technology are purported to be more efficient, precise, and objective than the human, it has become now widely known that the technologies are masking the reproduction of inequalities and social histories of sociopolitical violence; further indicating that maybe the human bar is not enough.”
Representation Is Not Enough To Create Ethically Fair And Politically Innocuous Artificial Intelligence
Dixon-Román addressed those in Milbank Chapel and those tuning in online, proposing that the formation of structures – whether artificial intelligence or something else – always involves the ‘utilizing of power’ and maintaining racial thought processes.
Dixon-Román posed a question one month after the fatal shooting of the 29-year-old Black man by Black police officers.
Dixon-Román went on to say:
“The question I’m wrestling with is if all we need are better representations, then I must ask, why does racial violence and subjugation persist, such as [in the case of] Tyree Nichols?”
“If representation and training data, data scientists or designers is what’s needed, then why does algorithmic bias continue even when these forms of representation are met?”
AI tools And Their Mathematics Are Built On Racial Logics From Colonialism And The Enlightenment.
Dixon-Román proposes that the creators of technology have been motivated by post-enlightenment ideals, such as universal reason and classification of people in terms of superiority, to reflect their inner feelings through the physicality of machines.
Dixon-Román, who joined TC from the University of Pennsylvania in January, explained.
Dixon-Román continues to say:
“Through cybernetics, man sought to instrumentalize interiority in the development of self-regulating, self-generating recursive systems of artificial intelligence.”
“Each phase of instrumentalizing interiority in exteriority was not simply with the desire of objective and impartial observations for reason, but with the interest of efficiency, reliability, speed, and maximizing of capital accumulation.”
Dixon-Román elucidates that certain principles can lead to erroneous conclusions in algorithmic governance, which can consequently result in the reinforcement of colonial ideals.
Measurement And Quantification Can Be Reimagined To Build Better Artificial Intelligence Tools
Dixon-Román and Lalitha Vasudevan, Vice Dean for Digital Innovation and Director of the Digital Futures Institute at TC, will collaborate to examine potential applications of AI in education.
The two plan to explore technology, ethics, and justice through the Gordon Institute and DFI collaboration. Teachers College is discussing this research and is well-equipped to head up the discourse on creating more justifiable technosocial futures.
The potential impact of artificial intelligence on race and bias is an important issue that must be addressed as we continue to develop and implement this transformative technology. While AI has the potential to mitigate racial biases and discrimination, it can also perpetuate and amplify them if not developed and deployed carefully.
It is crucial to recognize that AI is only as unbiased as the data and algorithms used to train and develop it. It is important to take a data-driven approach and ensure that AI is trained on diverse and representative data sets that accurately reflect the real-world population.
Source: www.tc.columbia.edu
