machine learning

Combating bias and creating more inclusive AI is unlikely to succeed unless developers include those people who have been historically excluded or ignored.

The wealth of data available to government today can be overwhelming. But is it useful? And if so, how do you generate useful analytic insights to support decision making?

What would you do if you had $2 million to invest in democracy in Australia? Last year, the Australian government awarded two organisations $1 million each under the Business Research Innovation and Investment Program.

Job losses aren’t the only dark side of automation. Account takeovers powered by credential stuffing are fast becoming the new black for cyber attackers hitting government.

Public sector responses to issues are traditionally reactive rather than anticipatory because of the time it takes to get good data. That’s changing rapidly as networks and machines literally start to think ahead.

Algorithms don’t do the right thing unless they are designed to, but creating ethical machine learning is no easy task, argues Data61’s Lachlan McCalman.

The Commonwealth’s behavioural economics team believes intelligent predictive computer programs can transform certain kinds of official decision making. But as always, the tool has to be applied with expertise and in the right situation.

We have the opportunity to start again, to resize and reshape the operations of the state around new technologies, argues the former UK digital head. Frankly, he says, if we don’t, they’ll do it to us.