AI progress is advancing at an ever increasing pace. Would you trust Siri to organise your next family trip? How about allowing Siri to cast your ballot in the next election? The more data we feed into the personalisation algorithms that surround us, the better the decisions they make on our behalf. Alphabet’s Chairman Eric Schmidt is convinced that advances in AI will make each and every human being in the world smarter, more capable and more accomplished. Yet the pace of AI progress brings challenges we must confront.Bias in algorithms can amplify our own biases and deepen social divisions. What is more, AI applications use data from our past actions to anticipate our needs in the future. This is problematic, because it tends to reproduce established patterns of behaviour, providing old answers to new questions. This form of algorithmic determinism is dangerous, because it precludes our need for experimentation and exploration, while ignoring the multiplicity of our identity.
Today’s citizens have the power to assemble online and it’s disrupting traditional political systems. The Internet has rewired civil society in unprecedented ways, propelling collective action to a radically new dimension. However, it has also given rise to right-wing populist movements such as Brexit in the UK and the rise of Donald Trump in the USA. Through the increasing polarisation of opinions online, the Internet has facilitated this development and has actually increased conflict and ideological segregation between opposing views, granting a disproportionate amount of clout to the most extreme opinions. Pressure from online activists can cause our democratically elected leaders to act in the strangest ways. In this blog post, I reflect on the effects of political polarisation on democracy and how social media has fuelled the dynamics of populism around the world.
Social influence is one of the most cited and yet least understood concepts in strategy and public policy today. While many people understand its critical importance in viral marketing campaigns, technology adoption, protest movements and other collective behaviours, there is little agreement on how it can be measured and harnessed for the greater good. So what methods and tools do we have for quantifying social influence? How can we design peer-to-peer interventions that make the most of digital technologies and the structural properties of social networks? In this post I review this and explore how we can leverage the dynamics of social influence to engineer social change.
The vast availability of digital traces of unprecedented form and scale has led many to believe that we are entering a new data revolution. Many argue that these new data sources and tools will allow us to improve research processes in transformative ways. However, it is important to be cognizant of the theoretical, methodological and practical challenges associated with such computational approaches, especially with regards to the role of the analyst, data access and distribution, and the critical role of theory in interpreting analytical outcomes. The more data is available, the more theory is needed to know what to look for and how to interpret what we have found. In this blog I set out to rethink the key challenges faced by big data researchers.
The EU referendum debate between the Remain and Leave camps is in full swing and all social media platforms are activated to win the race. For the past month, the Remain camp has been losing the battle online, while the Brexit campaign has been showing a masterful use of hashtags to dominate the debate in this corner of the Internet. How is the EU referendum debate is playing out on social media?