ALGORITHM IS GONNA GET YOU; WHAT THE RISE OF ALGORITHMS MEANS FOR PHILANTHROPY
18 January 2017
Algorithms are beginning to have a radical impact on society. Whether you believe this is for the better or the worse, it is also going to change our very understanding of philanthropy and civil society.
Discussions of trends in technology can often be seen within the media and the wider public as niche at best and irrelevant at worst – until suddenly they are not. One issue that has recently become much more prominent is the nature of the algorithms that underpin much decision making by artificial intelligence. This is in part due to allegations that they had a significant, even determinate effect on the recent US elections and in part due to claims that they represent both the cause of an apparent spike of ‘fake news’, and also the solution to that same problem.
Before we launch into an examination of these issues, it is worth taking a step back and trying to pin down exactly what we are talking about here. Algorithms are essentially a set of rules or a sequence of instructions. They utilise known information to advise a sequence of actions. We do this all the time intuitively. For example, experience has taught me that, unless I am planning to make a brave sartorial statement, it makes sense to put underwear on before my trousers.
The fact that people are using algorithms to gain a competitive advantage or to drive efficiency is by no means new. For a long time, number crunchers have analysed data to inform stock market strategy, the pricing of consumer goods, the cost of insurance and the efficacy of government policy choices and systems. However, rapid advances in computer processing power and the availability of huge amounts of data have enabled a far more widespread use of algorithms to identify trends and, crucially, to automate responses to those trends. In particular, the advent of ‘deep learning’ has led to algorithms which can effectively mimic many human decision making processes, but at a speed and scale that humans are simply not capable of. They also operate (at least in theory) in ways that are free from the false or lazy assumptions and prejudices that we all carry around with us.
In this way, the combination of big data and algorithms that can harness its potential is having a positive effect on many areas of contemporary society: from improving the efficacy of Google searches to making far more accurate weather predictions. Philanthropy will not be isolated from this trend: in fact, it is likely to be particularly affected given that it seeks to identify levers for and to institute positive societal change. However, as this article will show, the rise of algorithms presents as many challenges to philanthropy as it does opportunities. If one thing is for sure, it is that those interested in philanthropy must respond to the trend.
OPTIMISING THE ONLINE DONOR EXPERIENCE
Online donation is on a trajectory to become the dominant method of giving;particularly when you roll mobile into the equation. Of course, some people may still prefer to make cash donations – and there is good, if slightly unnerving evidence to suggest that some of our more base instincts particularly lend themselves to face to face fundraising. But the way we give online, the tools we use, the information we are shown and the way that online giving is integrated with social media will inevitably mean new opportunities for using machine learning to optimise the donor experience.
If you want to understand how algorithms are likely to impact on philanthropy then all you need to do is ask yourself one simple question: where is the data? One obvious place to start is with online donation portals. For example, algorithms which use social benchmarking (such as that used by Amazon), to show customers products that other people with similar viewing habits have visited, could be utilised to nudge donors towards more, and more diverse, giving. It is unlikely that we will have to wait too long to see this kind of profiling being used by giving portals. JustGiving, a fundraising portal in the UK, announced back in 2015 that when it came to collection they were taking “whatever we can get our hands on” including terabytes worth of web logs detailing the subsequent pages visited by donors and paying for processing power in the cloud to analyse it. It seems inevitable that donors will end up being shown information about causes which is ever-more tailored to their interests.
The matching of donors to causes is potentially a boon for both donors and the organisations that they support. A world in which donors are automatically introduced to information about how they can tackle issues about which they care deeply without their feeling intruded upon or harassed sounds like a charitable utopia. However, as anyone who has read any science fiction will know, we should be careful what we wish for.
As stated above, algorithms are not prejudiced. Unfortunately, people are (and yes, that includes donors). Given that algorithms designed to show us content we may be interested in work by crunching data about our habits and the habits of others ‘like us’; they tend to reflect those prejudices in the decisions they make. As a result, people who, for example, abhor racism but still hold unconscious biases, will not be shown content which might helpfully challenge that bias.
When it comes to the most advanced forms of machine learning, designed to tailor content that users are likely to respond to, the giants of social media reign supreme. As such, most people who work in fundraising and media roles for civil society organisations (CSOs) will be well aware that the success of their organisation’s social media profile is largely dependent on the way in which the algorithms which sit behind the platforms filter content for their audience.
Of course, giving people content that they are likely to appreciate is a pretty succinct way to summarise good business strategy; but it does also raise some fairly serious issues for the future of charitable giving and the causes it supports. Take Facebook for example, which, amongst other things, weights content that it shows based on what your friends find interesting. Given that humans are essentially fairly tribal creatures, we tend to connect strongly with people who share similar views (I am not going to get into the psychology of whether that relationship can be just as descriptive in reverse), meaning that what our friends find interesting can be an effective proxy for establishing our own interests. However, when it comes to raising awareness amongst people who are not already well-engaged, a system that is designed to reinforce group beliefs is ill-suited to challenging assumptions, promoting social change or reaching new donor audiences.
The fact that social media algorithms are creating information “echo chambers” is a problem for philanthropy not merely because it makes their own messaging and fundraising strategies more difficult, but because the failure to counter confirmation bias within groups and communities will likely lead to social issues that philanthropists and the organisations they support will subsequently have to address. In this way, algorithms may be creating a problem whilst simultaneously undermining our ability to solve it. Given that Facebook has announced plans to create their own in-house giving portal to allow donors to connect with causes and make donations entirely within Facebook, this is an issue that CSOs and the philanthropy community need to get to grips with urgently.
HEDGE FUND PHILANTHROPY
Our understanding of the way that donors respond to information about the impact of their donations is not complete, and it may well be that some of our assumptions are false: some studies have actually shown that donors give less when confronted with impact data, even when it is very positive. However, what is not in question is the increasing demand amongst donors and institutional funders for ever more data on impact. This is perhaps best demonstrated by a UK report which found that funder demand was the driving force behind increasing impact measurement, with only a mere 5 per cent of organisations indicating that service improvement was the main driver.