1. Progress Beyond the State of Art
In my deep dive into healthcare and the challenges posed by artificial intelligence (AI) and machine learning (ML), I have expanded my knowledge horizon by exploring the dimensions of algorithmic bias. Through an interdisciplinary lens, I have critically examined both individual- and group-level causality, unraveling the moral and ethical nuances of fairness, risk, and deservingness. My critique of existing fairness frameworks emphasizes their limitations and lays the groundwork for a more comprehensive approach to tackle the multifaceted nature of algorithmic bias. Drawing inspiration from the Fair Equality of Chances principle, as introduced by myself and colleagues, I have pioneered a unique perspective, showcasing how these biases, subtle yet profound, operate beyond overt discriminatory actions. My goal is clear: advocate for a holistic understanding of fairness in healthcare algorithms, emphasizing the recognition of biases and the moral quandaries they pose.
As I shared my specialized expertise on fairness in machine learning with POLIMI, it became a symbiotic relationship, enriching both the institution and strengthening my pedagogical skills. Drawing from my foundational background in ethics and aligning with my supervisor’s expertise in epistemology and probability, we fostered a multidisciplinary collaboration. This blossomed further through joint authorships with various researchers from diverse fields like mathematical statistics, computer science, and philosophy of science. Notably, collaborations with Dr. Francesco Nappo and Dr. Nicolò Cangiotti, among other esteemed peers from both European and US departments, have been instrumental in this integrative scholarly journey.
As I imparted my advanced competencies on fairness in machine learning to POLIMI, it was an exchange of knowledge, strengthening my teaching experience. My background in ethics, complemented by my supervisor’s strength in epistemology and probability, has paved the way for collaborative growth through the joint authorship of scientific articles.
While I faced resistance in traditional academic settings, my commitment has never waned. Venturing beyond academia, I am now harnessing my interdisciplinary knowledge to influence real-world scenarios, offering consultancy on fairness and AI to diverse stakeholders.
In reflection, my collaborations with Dr. Francesco Nappo and Dr. Nicolò Cangiotti, alongside other researchers from various European and US departments, have significantly contributed to our shared academic progress. Furthermore, the importance of AI ethics transcends academia. By offering AI ethics consultations to NGOs like Algorithmwatch and corporations, I’m directly influencing real-world applications. Additionally, recognizing the broader societal implications, I have made efforts to assist in governmental regulation activities by applying to serve as an expert for the ECAT office of the European Union. This endeavor represents my commitment to ensuring that advancements in AI are ethically sound and beneficial for all.