Tag: machine learning

‘Computer says no’: Is automation in the public interest?

Posted on by foluke.adebisi

By Kit Fotheringham, Bristol Doctoral College (University of Bristol)

Photo by Francisco De Legarreta C. on Unsplash

In common with many developed nations, the public sector in the UK takes up a sizable proportion of economic activity. Therefore, the way the public sector is run is of interest to the public, both as citizens, who expect good administration of public services, and as taxpayers, who contribute to public finances. Of course, not all citizens are taxpayers (especially children and those on low incomes), nor can all taxpayers be regarded as citizens (notably, companies). Some scholars even question whether the balance sheet of a sovereign government with its own currency is comparable to the household pocketbook, positing that government spending contributes to overall money supply. Nevertheless, politicians play to the narrative that public money is the collective property of taxpayers, and seeking to persuade voters that their policies will offer the best protection against further encroachment on the economic interests of individuals. (more…)

What are the main governance opportunities and challenges for procurement digitalisation?

Posted on by foluke.adebisi

by Professor Albert Sanchez-Graells, University of Bristol Law School.

Approximately a third of public sector spending goes to procure third-party goods, services, and works. Procurement rules and policies seek to ensure that contract awards are free from corruption, conflicts of interest or anticompetitive practices, and that these vast sums of public funds generate value for money and support social, environmental, and innovative practices. There is always room for improvement, though. The adoption of digital technologies is seen as a strategic catalyst for procurement reform, to increase the effectiveness of procurement regulation. Digitalisation could reduce the administrative burden through automation, generate data insights to inform policies and boost efficiency in public spending, and serve as a living lab for GovTech experimentation.

However, the transformative potential presumed in digital technologies generates hype and excessive expectations on the true size and nature of the achievable improvements. It also tends to overshadow the required groundwork and preparatory investment. New digital governance risks and requirements are not always recognised or understood. The growing public sector digital capability gap raises further obstacles. Heightened expectations and a minimisation of the challenges can get on the way of successful reform. In ongoing research funded by the British Academy, I apply an innovative technology-centred methodology to assess the governance opportunities and challenges for procurement digitalisation. This blog post provides a summary of the main findings so far. I will also be discussing them with a stellar panel on 15 December 2022 (details and registration). (more…)

AI & sustainable procurement: the public sector should first learn what it already owns

Posted on by lee.mcconnell

By Prof Albert Sanchez-Graells, Professor of Economic Law (University of Bristol Law School).

Photo credit: Flickr

While carrying out research on the impact of digital technologies for public procurement governance, I have realised that the deployment of artificial intelligence to promote sustainability through public procurement holds some promise. There are many ways in which machine learning can contribute to enhance procurement sustainability.

For example, new analytics applied to open transport data can significantly improve procurement planning to support more sustainable urban mobility strategies, as well as the emergence of new models for the procurement of mobility as a service (MaaS).* Machine learning can also be used to improve the logistics of public sector supply chains, as well as unlock new models of public ownership of eg cars. It can also support public buyers in identifying the green or sustainable public procurement criteria that will deliver the biggest improvements measured against any chosen key performance indicator, such as CO2 footprint, as well as support the development of robust methodologies for life-cycle costing.

However, it is also evident that artificial intelligence can only be effectively deployed where the public sector has an adequate data architecture.** While advances in electronic procurement and digital contract registers are capable of generating that data architecture for the future, there is a significant problem concerning the digitalisation of information on the outcomes of past procurement exercises and the current stock of assets owned and used by the public sector. In this blog, I want to raise awareness about this gap in public sector information and to advocate for the public sector to invest in learning what it already owns as a potential major contribution to sustainability in procurement, in particular given the catalyst effect this could have for a more circular procurement economy. (more…)