Edupolicy.ai's comprehensive analysis of artificial intelligence deployment reveals critical insights into the evolving landscape of technological governance. Our research indicates while AI solutions offer transformative potential across sectors, the implementation of these technologies demands rigorous oversight and ethical frameworks to ensure optimal outcomes. 

Through our research, we've identified that premature deployment of untested systems and over-reliance on historical data, can perpetuate systemic biases and create unintended consequences in decision-making processes.

Our investigation into automated systems has uncovered significant concerns regarding data inheritance patterns and their impact on contemporary algorithmic decisions. Edupolicy.ai's work seeks to uncover intentional and inadvertent technological misuse.  We work to established new benchmarks for safety protocols in AI development.  Uncovering proactive harm prevention through our robust ethical review processes, comprehensive pre-deployment testing, and continuous monitoring systems represents the gold standard in responsible AI development.

Drawing from our extensive collaboration with tech, corporate and industry leaders, we recognize that while some organizations have implemented exemplary safeguards, the inconsistent application of these practices across the sector still demands careful attention. 

We advocate for a balanced approach which harmonizes innovation with public protection; seeking to work with automated systems to make sure they undergo rigorous testing and continuous evaluation to meet intended outcomes while safeguarding against foreseeable risks. 

Our experience conclusively demonstrates that implementing comprehensive protective measures not only enhances public confidence; but, also creates a more stable environment for technological advancement.

Some of the best examples can be found in the "AI Bill of Rights: Making Automated Systems  Work For The American People." Released by the The White House in October of 2022.  We seek to highlight these kinds of examples referenced below in the AI Bill of Rights as ways that we must seek to remedy in our tech and society.  

Examples Below From: AI Bill of Rights Include:  "A proprietary model was developed to predict the likelihood of sepsis in hospitalized patients and was implemented at hundreds of hospitals around the country. An independent study showed that the model predictions underperformed relative to the designer’s claims while also causing ‘alert fatigue’ by falsely alerting likelihood of sepsis."

"On social media, Black people who quote and criticize racist messages have had their own speech silenced when a platform’s automated moderation system failed to distinguish this “counter speech” (or other critique and journalism) from the original hateful messages to which such speech responded."

"A device originally developed to help people track and find lost items has been used as a tool by stalkers to track victims’ locations in violation of their privacy and safety. The device manufacturer took steps after release to protect people from unwanted tracking by alerting people on their phones when a device is found to be moving with them over time and also by having the device make an occasional noise, but not all phones are able to receive the notification and the devices remain a safety concern due to their misuse."

"An algorithm used to deploy police was found to repeatedly send police to neighborhoods they regularly visit, even if those neighborhoods were not the ones with the highest crime rates. These incorrect crime predictions were the result of a feedback loop generated from the reuse of data from previous arrests and algorithm predictions."

Deepfakes as they are commonly referenced as, "AI-enabled “nudification” technology that creates images where people appear to be nude—including apps that enable non-technical users to create or alter images of individuals without their consent—has proliferated at an alarming rate. Such technology is becoming a common form of image-based abuse that disproportionately impacts women. As these tools become more sophisticated, they are producing altered images that are increasingly realistic and are difficult for both humans and AI to detect as inauthentic."

"A company installed AI-powered cameras in its delivery vans in order to evaluate the road safety habits of its drivers, but the system incorrectly penalized drivers when other cars cut them off or when other events beyond their control took place on the road. As a result, drivers were incorrectly ineligible to receive a bonus."

Abstract:  

As AI permeates higher education, faculty resistance emerges as a critical philosophical quandary. It calls us to question the essence of teaching and learning in the 21st century. 

Can the art of teaching, rooted in empathy and adaptability, be entrusted to algorithms? How do we navigate AI integration while upholding the timeless values of our profession? This presentation embarks on a philosophical exploration of faculty resistance to AI, seeking not only pragmatic solutions but also a deeper understanding of what it means to educate in an era of intelligent machines. 

Join us in imagining a future where human wisdom and AI intertwine.

Abstract:  

As AI becomes increasingly prevalent on college campuses, it is crucial that we come together as a higher education community to ensure its responsible and ethical use. In this presentation, we will dive into the complex considerations surrounding AI governance in academia. 

We'll discuss the potential risks and unintended consequences of AI and explore the policy frameworks and decision-making structures needed to mitigate them. Through candid dialogue and shared learning, we'll grapple with questions of privacy, bias, autonomy, and more. 

Participants will leave with a deeper understanding of the ethical dimensions of AI and concrete strategies for shaping its adoption in ways that align with our values and advance our missions. Join us for this vital conversation.