History and philosophy of science (HPS) is an ideal way to critically engage with science and its social and cultural significance. Any student with a genuine interest in science will derive benefit from the study of this discipline.
Teaching staff in the School of History and Philosophy of Science have published widely in their fields of expertise and have gained international recognition for their research. This makes them fantastic educators, sharing their knowledge and experiences in the classroom so students can be at the forefront of innovations in the field.
The University of Sydney is ranked first in Australia and fifth in the world for graduate employability.* This stems from our immersive, research-led teaching which prepares students for the real-world and a successful career.
Congratulations to Hans Pols now a Fellow of the Royal Society of NSW. Hans will present a public lecture " Physicians as Public Intellectuals: Indonesian Physicians in the Dutch East Indies" September 4th 2019. Details Here
Assistant Professor Sara Langston
Asst. Professor, Spaceflight Operations, Embry-Riddle Aeronautical University
University of Sydney, Ph.D History and Philosophy of Science; Awarded the Science Faculty Postgraduate Research Prize for Outstanding Academic Achievement.
As NASA celebrates the 50th anniversary of the historic Moon landing with a live TV broadcast and events, there is a focus on recognizing the contributions of the thousands of men and women who made the Apollo 11 mission possible. This year is particularly significant for the legacy of the Apollo program because of the president’s Space Policy Directive 1, which tasks NASA with returning to the Moon by 2024. This time, the mandate requires establishing a permanent lunar base and advancing space exploration to Mars and across the solar system. Read More
The nascent field of moral AI asks how best to ensure that artificially intelligent (AI) systems instantiate and promote human moral norms and values. A growing number of proposals have suggested that the best way to achieve this objective is by developing artificial moral cognition, that is, artificial systems that recognize and respond to situations of moral significance. However, extant approaches involve building sophisticated cognitive architectures into these artificial systems, resulting in intractable frameworks. I present a new technical framework for modeling artificial moral cognition. Specifically, I propose to use reinforcement learning-based environments that teach artificial systems to learn, value, and respond to moral content and contexts. To illustrate the view, I describe a basic “moral gridworld,” designed to model the moral cognitive capacity of fairness, here quantified in terms of the Ultimatum Game. I then discuss a suite of variations that can be introduced into the gridworld to represent a range of moral cognitive features, including cross-cultural variability and the simulation of signature moral dilemmas
Monday 21st October 2019
Level 5 Function Room,
Administration Building (F23)