All Keynote speakers will be streamed as part of the Internet Festival event:
Misinformation on social media abounds, and computational approaches alone have not been able to stem its tide. As a complementary approach, I describe the power of correction of misinformation on social media, whether it comes from peers, platforms, or experts. Results from multiple experiments, dealing with a variety of health issues, and on four different social media platforms demonstrate that correction does generally lead people to update their beliefs. Best practices for correction will also be discussed and illustrated.
Sternberg Family Distinguished University Professor. Director, Network Science Institute. Northeastern University, Boston MA
The data science revolution is finally enabling the development of large-scale data-driven models that provide scenarios, forecasts and risk analysis for infectious disease threats. These models also provide rationales and quantitative analysis to support policy making decisions and intervention plans. At the same time, the non-incremental advance of the field presents a broad range of challenges: algorithmic (multiscale constitutive equations, scalability, parallelization), real time integration of novel digital data streams (social networks, participatory platform, human mobility etc.). I will review and discuss recent results and challenges in the area, and focus on ongoing work aimed at responding to the COVID-19 pandemic.
Every day we see news about advances and the societal impact of AI. AI is changing the way we work, live and solve challenges but concerns about fairness, transparency or privacy are also growing. Ensuring an ethically aligned purpose is more than designing systems whose result can be trusted. It is about the way we design them, why we design them, and who is involved in designing them. If we are to produce responsible trustworthy AI, we need to work towards technical and socio-legal initiatives and solutions which provide concretise instructions, tools, and other means of dictating, helping, and educating AI practitioners at aligning their systems with our societies’ principles and values.
Bruno Kessler Foundation
The almost universal adoption of mobile phones, the exponential growth in the usage of Internet services and social media platforms, and the proliferation of digital payment systems, wearable devices, and connected objects has led to the existence of unprecedented amounts of data about human behavior. Thus, we live in an unprecedented historic moment where the availability of vast amounts of behavioral data, combined with advances in machine learning, are enabling us to build predictive computational models of human behavior. In my talk, I will show examples of how those computational models of human behavior can be used to better understand and to design more efficient companies, cities, and societies, For example, I will present some recent works where we have leveraged mobile phone data, credit card transactions, Google Street View images, and social media data in order (i) to infer how vital and livable a city is, (ii) to find the urban conditions that magnify and influence urban life, (iii) to study their relationship with societal outcomes such as poverty, criminality, innovation, segregation, and (iv) to envision data-driven guidelines for helping policy makers to respond to the demands of citizens. Finally, I will also discuss key human-centric requirements for a positive disruption of these novel approaches including a fundamental renegotiation of user-centric data ownership and management, the development of tools and participatory infrastractures towards increased algorithmic transparency and accountability, and the creation of living labs for experimenting and co-creating data-driven policies.