Digitalisation, big data and policymaking

How will artificial intelligence and big data change policymaking? (Source: http://sloanreview.mit.edu/article/can-artificial-intelligence-replace-executive-decision-making/)

Confidence in national governments across OECD countries had waned to an all-time low of 40%  in 2014. Trust in parliaments among the same sample nowhere surpasses 45% [1]. As for Americans, the trust they carry for their federal government has fallen from approximately 75% to 20% over the past twenty years [2].

Public Trust in Government: 1958-2015, Nov. 23rd, 2015, Pew Research Centre, accessed March 7th 2017, http://www.people-press.org/2015/11/23/public-trust-in-government-1958-2015/

This can be explained by a substantial mistrust between governments and citizens, much of which stems from a lack of communication. Governments are often criticised for their incapacity to provide viable and long-term solutions to citizens’ needs. Likewise, citizens have no clear understanding of what governments actually accomplish.

These communication failures, when analysed in more detail, can be split into three clear points of friction:

  1. A lack of efficient use of public services, due to difficult access and time strains;
  2. A lack of transparency and accountability vis-à-vis public institutions;
  3. A lack of participatory platforms, which would allow shared governance, the building of strong community networks, in turn fostering trust among citizens themselves.

What can be done to bridge the gap between governments and those they are meant to serve? Further, to what extent can we turn to digitalisation and current innovations in artificial intelligence to reach a powerful and efficient solution?

 

Trends of Today, Solutions of Tomorrow

Let’s first look at the technology trends. These have actively been shaping the way people relate to one another, and how data may be gathered and made sense of. By way of example, Messenger and WhatsApp are used three times more often than phone texts on a daily basis: 60 billion times for both internet-based services, as opposed to a mere 20 billion SMS. Every minute, over 98,000 tweets are sent, 695,000 Facebook statuses are posted and 217 new mobile web users see the light of day. A startling 6.1 billion smartphones are expected to be in use by 2020.

(Source: Ericsson Mobility Report – June 2015, https://www.slideshare.net/Ericsson/ericsson-mobilityreportjune2015)

With this trend comes the new and not-yet fully grasped power of artificial intelligence, where machines accumulate information about users to provide personalised and instantaneous answers to queries. As this develops, barriers to interaction break loose. Any information is accessible to all in a concise and infinitely faster way than ever before. All losses, economic and non-economic, stemming from browsing the Internet and making sense of many website pages will disappear.

Finally, Big Data. The instantaneous collection of millions of observations on what we eat, what we like and dislike, but also what we want and hope to receive, opens the possibility for near-perfect evidence-based policymaking. Restrictions on sample size need no longer be an issue, while policy responses will be tailored to specific population needs.

In very real terms, this would be a world where queuing to receive specific information would no longer exist. Information about one’s access to unemployment benefits, or the necessary process to register to vote — to only name a few examples — could be transmitted in record time on a smartphone. Citizens could have direct information with regards to the laws, the implementation of a policy in one’s neighbourhood and Members of Parliament’s personal wealth and potential conflicts of interest.

 

What This Means for Governments

On the side of administrative authorities, public savings would abound. According to the Cabinet Office, the UK government saved £1.7 billion through digital and technology transformation in 2015 only, and £3.56 billion in the 2012-2015 period. Individuals’ interactions with governmental agencies through digital services are twenty times cheaper than a phone call, and fifty times cheaper than face-to-face meetings.

The outcomes of such innovative reforms are manifold: increasing returns to scale as well as a precise allocation of public services through big data analytics or direct reporting from citizens; and, perhaps more importantly, a better understanding of what citizens actually need and expect from their governments. From a more overarching perspective, digitalisation enables the building of stronger community networks and strengthens the trust in public institutions, issues that appear to be at the heart of many citizens’ true concerns in today’s environment.

 

What To Take Away

New technologies have their flaws, many of which we must approach and tackle with great seriousness, notably with regards to confidentiality and privacy. States and supranational entities (think of the EU’s “Safe Harbour” policy) are starting to investigate potential drawbacks with great attention. Nonetheless the power of such solutions is immense and must not be underestimated. Big data analytics today stands at infant stage: but the size of the datasets to come — in turn providing the necessary information for tailored policies — is incommensurable. Turning our back to such technologies, or setting them aside on claims that “it is not yet the real world”, is the worst mistake policy-makers, national governments and interest-groups can make today.

 


[1] Trust in Government, OECD, accessed March 7th 2017, http://www.oecd.org/gov/trust-in-government.htm

[2] Public Trust in Government: 1958-2015, Nov. 23rd, 2015, Pew Research Centre, accessed March 7th 2017, http://www.people-press.org/2015/11/23/public-trust-in-government-1958-2015/


Hélène Procoudine-Gorsky is an MPA candidate at LSE, originally from Paris. Before joining LSE, Hélène completed a BSc in Business Management and Administration and a Masters in Finance at Université Paris Dauphine. Hélène has professional experience in investment banking with UBS and Société Generale.

Théo Bourgery is a first-year MPA student at LSE, originally from France. He received an Honours Bachelor of Arts in Sociology and Economics from McGill University. Prior to LSE, Théo was a political appointee to a French MP, in charge of parliamentary affairs. He also interned for the French ministries of Justice and Defence.

Siddharth Rajgopalan is a first-year MPA student at LSE, originally from India. He completed a Bachelor of Engineering from the National University of Singapore. Prior to LSE, Siddharth was working in strategic partnership development roles at technology and sustainability related start-ups in Singapore. 

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