We are creating some awesome events for you. Kindly bear with us.

Tackling the ethics of data science through conference

The University of Sydney hosted a conference on the ethics of data science, bringing together world-renowned experts to address the current crisis in confidence around machine learning, artificial intelligence (AI) and data use.

As reported, self-driving cars, automated personal assistants and domestic violence, and how they each relate to data and artificial intelligence, were just some of the topics up for debate.

AI affecting daily lives

Undeniably, data and AI are well on their way to affecting every facet of the people’s daily lives.

For instance, industries and government are already relying on machine learning to make important decisions that will have a real effect on the lives of consumers and citizens.

Algorithms are a fundamental tool in everyday machine learning and artificial intelligence, but experts have identified a number of ethical problems.

One problem would be how models built with biased and inaccurate data can have serious implications and dangerous consequences.

These consequences range from the legal and safety implications of self-driving cars and incorrect criminal sentencing, to the use of automated weapons in war.

The conference’s speakers, who came from diverse disciplines such as ethics, law, and AI, discussed the current research and practice relating to the ethics around algorithms.

They identified solutions for creating a new generation of ethical data science techniques.

Using data to end domestic violence

Centre for Translational Science data expert, Dr Roman Marchant, believes that there needs to be a more concerted effort between government and private institutions in using data to better understand criminality and put an end to domestic violence.

The world is at a point in history where a world of data is within our fingertips. However, the complexity of issues such as criminology will always be bigger than any amount of data currently available.

Tackling criminal behaviour and understanding the drivers behind it require building truly multidisciplinary partnerships between data scientists and experts in criminology.

Efforts should be focused on understanding the problem in order to reduce or eliminate crime. Like with any crime, there are specific levers and influences which lead to a person committing domestic violence.

How AI can influence data

Director of the Centre for Translational Data Science, Professor Sally Cripps, believes data experts must understand how to quantify uncertainty to prevent bias.

Notably, algorithms per se are not unethical; the issue lies in the bias in sampling that is created by some implementations of the algorithms.

If an algorithm finds that a subgroup of the population is more likely to experience domestic violence, and on that basis continues to sample from that subgroup, then it is a self-fulfilling prophecy.

To guard against this, a deep understanding of uncertainty and how to quantify it needs to be incorporated into algorithms.

About the Centre

The Centre for Translational Data Science uses data science to preserve natural resources, build intelligent systems, improve digital health and explore the human condition.

Hosting experts from across a diverse range of disciplines, it tackles important research questions, applying innovation and translation, application and foundations to find solutions and ensure real-world impact.

Send this to a friend