By Professor Albert Sanchez-Graells, Professor of Economic Law and Co-Director of the Centre for Global Law and Innovation (University of Bristol Law School)
Preventing, detecting, and sanctioning corruption in public procurement is one of the main goals of all systems of regulation applicable to the expenditure of public funds via contract (see eg Williams-Elegbe, 2012). Despite constant and regularly renewed efforts to fight procurement corruption at an international (such as the UN Convention against Corruption, or the 2016 OECD’s Preventing Corruption in Public Procurement report) and domestic level (see eg the UK’s 2020 ‘Local government procurement: fraud and corruption risk review’), corruption remains a pervasive problem in any given jurisdiction. Of course, there are different forms and degrees of corruption infiltration in different procurement systems but – if any evidence was needed that no system is corruption-free – pandemic-related procurement served as a clear reminder that this is the case (see eg Transparency International, 2021; as well as Good Law Project v Cabinet Office  EWHC 1569 (TCC)). It should then not be surprising that the possibility that artificial intelligence (AI) could ‘change the rules of the game’ (eg Santiso, 2019) and bring procurement corruption to an end is receiving significant attention. In a recent paper*, I critically assess the contribution that AI can make to anti-corruption efforts in the public procurement context and find that, while it could make a positive incremental contribution, it will not transform this area of regulation and, in any case, AI’s potential is significantly constrained by existing data architectures and due process requirements.(more…)
By Prof Albert Sanchez-Graells, Professor of Economic Law and Member of the Centre for Health, Law, and Society (University of Bristol Law School)
On 30 September, the Centre for Health, Law, and Society had the honour of hosting an excellent panel of speakers for a webinar on ‘Healthcare procurement and commissioning during Covid-19: reflections and (early) lessons’. The speakers provided short presentations on a host of very complementary issues surrounding the reaction of NHS procurement and commissioning to the COVID-19 challenges. The ensuing discussion brought to light a number of general themes that are, by and large, aligned with the worries that others and I had expressed at the outset of the pandemic*, and a number of challenges that will shape the readjustment or reregulation of NHS procurement and commissioning in the medium and long term.
This blogpost initially provides some brief notes on the most salient points made by the speakers in their presentations, which do not aim to be exhaustive. It then goes on to offer my own reflections and views on what lessons can be extracted from the procurement and commissioning reaction to the first wave of Covid-19, which do not necessarily represent those of the panel of speakers. (more…)
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…)