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Both are ACEMS researchers based at Monash University’s Department of Econometrics and Business Statistics.

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All six featured in the top 100 places of the annual survey ranking 200 universities worldwide, with the University of Melbourne at #39. The University of Sydney, ANU, University of Queensland, Monash and UNSW were also recognised in this year’s rankings.

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In April, as the coronavirus pandemic was gathering force around the world, reporters asked Brendan Murphy, then Australia鈥檚 Chief Medical Officer, about international case numbers. In his answer, he made an interesting comment:

The only numbers I have total faith in are the Australian numbers.

鈥淔aith鈥� might seem an odd word to use about about official statistics. But in our research, which involves talking to statisticians, public servants and journalists who produce and communicate the statistics that govern our lives, people say overwhelmingly that faith and trust are essential parts of what makes statistics useful.

Despite the objective and impartial appearance of statistics, it is a web of people and human processes that makes them trustworthy.

When trust falters

The COVID-19 pandemic has shown us the importance of numbers we can rely on. In many cases, early problems in data management have been indicators of bigger problems to come.

In the United Kingdom, a lack of local case data was hindering public efforts . By October, it emerged that some from national reporting due to sloppy data management.

In Australia, the quality of COVID-19 responses in different states has broadly reflected of the quality of each state鈥檚 published data.

New South Wales was celebrated early on by data scientists for its and in data management, long before Prime Minister Scott Morrison鈥檚 September comment that the state鈥檚 contact tracing was the 鈥溾��.

Meanwhile, inconsistencies in Victoria鈥檚 data management 鈥� such as irregular definitions of 鈥渓ocal鈥� and 鈥渃ommunity鈥� transmission, and confusion over the definition of 鈥溾�� 鈥� were back in June, before the state鈥檚 mystery cases blew up into a second wave.

Governing by numbers

Public statistics play a huge role in our lives. Political staffers we have interviewed in our research explained how the 鈥渕ere presence of any kind of numbers鈥� seems to make people more trusting of any claim.

Enthusiasm for often relies on the image of statistics having what philosophers call 鈥溾��. By this logic, statistical results are essentially produced by machines or mechanical processes, so decisions based on data can be routine, apolitical, unbiased and incontestable.

But talking to the people behind our national numbers reveals how official statistics are in fact the product of expertise, immense resources, personal judgement calls, and trust.

Analysts we spoke to described official statistics as 鈥渋cebergs鈥� concealing vast tangles of sources and stories. Statisticians often used words like 鈥渋nstinct鈥� and 鈥渧ibe鈥� in explaining how they check data sources and rely on long-term relationships to gather figures. One public servant summed up the situation neatly:

A lot of personal relationships are stringing together government statistical work.

The process of transforming real life into tables of data takes expert human intervention at every stage. These interventions can result in vastly different answers to the same initial questions. As the answers often form the bedrock of public decision-making, it becomes crucial we can trust the people who make the decisions behind the scenes.

鈥淭otal faith鈥� in Australian numbers

When the Statistical Society of London was founded in 1834, discussion of interpretation or 鈥渙pinion鈥� was at its meetings. Modern statisticians have a much greater understanding of the importance of how people feel about data: the theme of this year鈥檚 was 鈥淐onnecting the world with data we can trust鈥�.

But trusting 鈥渄ata鈥� buries the work of the people who create statistics. In practice, they are the ones we are trusting.

In Australia, at least, we trust them a lot. Murphy鈥檚 鈥渢otal faith鈥� in 鈥淎ustralian numbers鈥� is reflected in a conducted by the Australian Bureau of Statistics, which found 85% of the general community trust ABS statistics. The figure is even higher among 鈥渋nformed users鈥�: a near-unanimous 99%.

Our communal faith in the numbers produced by the ABS reflects a web of trust and relationships built over decades.

Why trust matters

For many policy issues, such as unemployment, ABS statistics are taken as our absolute measure of reality. In these cases, the fact that 99% of informed users trust the numbers is what lets government and society keep functioning.

ABS data forms a shared basis for discussion. One analyst told us it鈥檚 not just trust in the bureau鈥檚 expertise that creates trust in the data 鈥� it鈥檚 also 鈥渂ecause everybody else is using it as well鈥�.

Those who work with public statistics agree these networks of trust 鈥� both between institutions like the ABS and the Australian public, and between individual academics, public servants, statisticians and journalists 鈥� rely on day-to-day honesty and responsiveness.

Transparency and consistency are essential. Statisticians and journalists alike emphasised that even data formatting plays a role in building trust. One journalist we interviewed talked about a health agency releasing coronavirus statistics as PDF files emailed to a private list early in the pandemic, describing it as 鈥渁 ridiculous situation鈥� that created extra work for the journalist to make the numbers clear and accountable in public. (State governments have since improved on this, generally making daily case numbers publicly available online.)

Long-term trust

Our response to future crises, whether the next pandemic or the impacts of climate change, will rely on the strong communal web of trust in our statistics.

Statistical failures, like the UK or the United States coronavirus deaths, damage public trust in government. When institutions can prove their statistics are , the public are more willing to follow directives based on those statistics.
How do we know we can trust statistics? We talked to the humans behind the numbers to find out

, PhD candidate, ; , Associate Professor, , and , Senior Lecturer, Australian National Centre for the Public Awareness of Science,

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After days of speculation, today鈥檚 by Victorian Premier Daniel Andrews was pretty much as we expected: a significant lifting of restrictions, albeit only a half-step out of lockdown.

From 11.59pm tonight, Melburnians will be able to travel up to 25km from home, with no time limits on exercise or recreation, bringing the chance to play a round of golf or visit the hairdresser.

Even more encouragingly, we may only have to wait a week until the lockdown is lifted, the 鈥渇our reasons鈥� to leave home are removed, and retailers and other businesses can once again open their doors.

Andrews said the planned move to step three of the COVID-19 roadmap could be brought forward a week from its provisional date of November 1 if case numbers 鈥� now tracking at 7.5 new cases a day for metropolitan Melbourne and just 0.5 in the regions 鈥� remain favourable.

鈥淰ictorians have stayed the course, and we just have a little longer to go,鈥� he said.

I agree Victorians can rightly be proud, because this lockdown was a very big ask. In fact, I see no reason why we can鈥檛 remove blanket rules such as the 25km radius and Melbourne鈥檚 鈥渞ing of steel鈥� immediately.

Buying time

The blanket restrictions in Melbourne, which have been in place since early July, have bought time to rebuild our public health response, with stronger measures for testing, contact tracing and isolating outbreaks. The idea is to 鈥渂ring the restrictions to the virus鈥�, meaning we can now contain it wherever it might appear.

As a result, restricting the general public鈥檚 movements with the help of blanket rules makes less sense, because many Melburnians now have a minuscule risk.

I don鈥檛 understand why we need to impose a 25km limit. It鈥檚 such a big radius but will still exclude people who live at opposite ends of the city from seeing each other. Perhaps the fear is too many people will congregate in popular or scenic places. But surely that can be managed by scrutinising those particular places.

In contrast, when Singapore was coming off its second wave, it lifted restrictions when COVID-19 cases were at 60 per million people, per day. Melbourne鈥檚 current average is just over 1 case per million people, per day. If Andrews were to promote Victoria鈥檚 strategy to the rest of the world, I鈥檝e no doubt they would agree it鈥檚 been a success, but they would probably also wonder why it is taking so long.

We had an extended blanket lockdown that was enough to quash the virus multiple times over in households. But we weren鈥檛 able to contain it in aged care, certain workplaces, and complex households.

With cases now so low, the idea that all public movement equals viral spread is not true. There鈥檚 a lot more to this virus than this sort of reductionist approach. We know probably 70% of people don鈥檛 even pass it on, and that many cases are the end of a chain of infection. If we do get a cluster, we will likely pick it up. This gives me confidence Melbourne will be able to open up fully next weekend.

The wholesale rebuilding of our contact-tracing means we are now very much on the front foot. Health authorities should continue urgently interrogating and isolating new cases, particularly mystery ones.

But for the wider public, it is now important to instil a sense that the government trusts people to be sensible for themselves. The more rules we have, the harder it is for people to have a sense of agency.

The rules should now be focused on areas where there is greatest risk. Unnecessary blanket rules might get in the way of people buying in. For instance, the ring of steel shouldn鈥檛 be necessary, given the testing and tracing measures we now have in place. What鈥檚 more, I think it will be a long time before people go back to their old patterns of movement, given that people have become acclimatised to staying at home.

This also means it鈥檚 easier to consider lifting border restrictions. While we鈥檝e been busy fighting off the second wave we鈥檝e built the health response to a point where we can live with the virus. So things like borders become less crucial.

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If authorities aren鈥檛 busy policing things that don鈥檛 make much of a difference, such as the 25km rule, it will free up resources and also mean people have one less rule, and one less fine, hanging over them.

I would also urge authorities to allow people to wear masks only in situations where it makes a real difference, as opposed to everywhere. It鈥檚 easier to trust the public to do that when they鈥檙e not being told to wear them all the time.

Over more than three months, Victorians have grown used to being told what to do in intense detail. Now it鈥檚 time for people to get back some control, and I鈥檓 hopeful we can do that in a way that鈥檚 safe.

, Chair in Epidemiology,

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by the University of Adelaide’s and 聽of the is part of ‘The Conversation’鈥檚 series on the science of free will.

Have you ever watched a video or movie because YouTube or Netflix recommended it to you? Or added a friend on Facebook from the list of 鈥減eople you may know鈥�?

And how does Twitter decide which tweets to show you at the top of your feed?

These platforms are driven by algorithms, which rank and recommend content for us based on our data.

As Woodrow Hartzog, a professor of law and computer science at Northeastern University, Boston, :

If you want to know when social media companies are trying to manipulate you into disclosing information or engaging more, the answer is always.

So if we are making decisions based on what鈥檚 shown to us by these algorithms, what does that mean for our ability to make decisions freely?

Social media algorithms, artificial intelligence, and our own genetics are among the factors influencing us beyond our awareness. This raises an ancient question: do we have control over our own lives? This article is part of The Conversation鈥檚 series on the science of free will.

Have you ever watched a video or movie because YouTube or Netflix recommended it to you? Or added a friend on Facebook from the list of 鈥減eople you may know鈥�?

And how does Twitter decide which tweets to show you at the top of your feed?

These platforms are driven by algorithms, which rank and recommend content for us based on our data.

As Woodrow Hartzog, a professor of law and computer science at Northeastern University, Boston, :

If you want to know when social media companies are trying to manipulate you into disclosing information or engaging more, the answer is always.

So if we are making decisions based on what鈥檚 shown to us by these algorithms, what does that mean for our ability to make decisions freely?

What we see is tailored for us

An algorithm is a digital recipe: a list of rules for achieving an outcome, using a set of ingredients. Usually, for tech companies, that outcome is to make money by convincing us to buy something or keeping us scrolling in order to show us more advertisements.

The ingredients used are the data we provide through our actions online 鈥� knowingly or otherwise. Every time you like a post, watch a video, or buy something, you provide data that can be used to make predictions about your next move.

These algorithms can influence us, even if we鈥檙e not aware of it. As the New York Times鈥� explores, YouTube鈥檚 recommendation algorithms can drive viewers to , potentially leading to online radicalisation.

Facebook鈥檚 News Feed algorithm ranks content to keep us engaged on the platform. It can produce a phenomenon called 鈥溾��, in which seeing positive posts leads us to write positive posts ourselves, and seeing negative posts means we鈥檙e more likely to craft negative posts 鈥� though this study was partially because the effect sizes were small.

Also, so-called 鈥溾�� are designed to trick us into sharing more, or on websites like Amazon. These are tricks of website design such as hiding the unsubscribe button, or showing how many people are buying the product you鈥檙e looking at right now. They subconsciously nudge you towards actions the site would like you to take.

You are being profiled

Cambridge Analytica, the company involved in the largest known Facebook data leak to date, claimed to be able to based on your 鈥渓ikes鈥�. These profiles could then be used to target you with political advertising.

鈥淐ookies鈥� are small pieces of data which track us across websites. They are records of actions you鈥檝e taken online (such as links clicked and pages visited) that are stored in the browser. When they are combined with data from multiple sources including from large-scale hacks, this is known as 鈥溾��. It can link our personal data like email addresses to other information such as our education level.

These data are regularly used by tech companies like Amazon, Facebook, and others to build profiles of us and predict our future behaviour.

You are being predicted

So, how much of your behaviour can be predicted by algorithms based on your data?

Our research, , explored this question by looking at how much information about you is contained in the posts your friends make on social media.

Using data from Twitter, we estimated how predictable peoples鈥� tweets were, using only the data from their friends. We found data from eight or nine friends was enough to be able to predict someone鈥檚 tweets just as well as if we had downloaded them directly (well over 50% accuracy, see graph below). Indeed, 95% of the potential predictive accuracy that a machine learning algorithm might achieve is obtainable just from friends鈥� data.

Our results mean that even if you #DeleteFacebook (which trended after the ), you may still be able to be profiled, due to the social ties that remain. And that鈥檚 before we consider the things about Facebook that make it so anyway.

We also found it鈥檚 possible to build profiles of non-users 鈥� so-called 鈥溾�� 鈥� based on their contacts who are on the platform. Even if you have never used Facebook, if your friends do, there is the possibility a shadow profile could be built of you.

On social media platforms like Facebook and Twitter, privacy is no longer tied to the individual, but to the network as a whole.

No more free will? Not quite

But all hope is not lost. If you do delete your account, the information contained in your social ties with friends grows stale over time. We found predictability gradually declines to a low level, so your privacy and anonymity will eventually return.

While it may seem like algorithms are eroding our ability to think for ourselves, it鈥檚 not necessarily the case. The evidence on the effectiveness of psychological profiling to influence voters .

Most importantly, when it comes to the role of people versus algorithms in things like spreading (mis)information, people are just as important. On Facebook, the extent of your exposure to diverse points of view is more closely related than to the way News Feed presents you with content. And on Twitter, while 鈥渇ake news鈥� may spread faster than facts, it is , rather than bots.

Of course, content creators exploit social media platforms鈥� algorithms to promote content, on , and other platforms, not just the other way round.

At the end of the day, underneath all the algorithms are people. And we influence the algorithms just as much as they may influence us.

, Senior Lecturer in Applied Mathematics and , Associate Professor, Mathematics & Statistics,

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