I have started to watch the three-session series on Intelligent Automation in US Federal Procurement hosted by the GW Law Government Procurement Law Program over the last few weeks (worth watching!), as part of my research for a paper on AI and corruption in procurement. The first session in the series focuses in large part on the intelligent automation of information gathering for the purposes of what in the EU context are the processes of exclusion and qualitative selection of economic providers. And this got me thinking about how it would (or not) be possible to replicate some of the projects in an EU jurisdiction (or even at EU-wide level).
And, once again, the issue of the lack of data on which to train algorithms, as well as the lack of representative/comprehensive databases from which to automatically extract information came up. But somehow it seems like the ESPD and the underlying regulatory approach may be making things more difficult.
In the EU, automating mandatory exclusion (not necessarily to have AI adopt decisions, but to have it prepare reports capable of supporting independent decision-making by contracting authorities) would primarily be a matter of checking against databases of prior criminal convictions, which is not only difficult to do due to the absence of structured databases themselves, but also due to the diversity of legal regimes and the languages involved, as well as the pervasive problem of beneficial ownership and (dis)continuity in corporate personality.
Similarly, for discretionary exclusion, automation would primarily be based on retrieving information concerning grounds not easily or routinely captured in existing databases (eg conflicts of interest), as well as limited by increasingly constraining CJEU case law demanding case-by-case assessments by the contracting authority in ways that diminish the advantages of automating eg red flags based on decisions taken by a different contracting authority (or centralised authority).
Finally, automating qualitative selection would be almost impossible, as it is currently mostly based on the self-certification implicit in the ESPD. Here, the 2014 Public Procurement Directives tried to achieve administrative simplification not through the once only principle (which would be useful in creating databases supporting automatisation of some parts of the project, but on which a 2017 project does not seem to have provided many advances), but rather through the ‘tell us only if successful’ (or suspected) principle. This naturally diminishes the amount of information the public buyer (and the broader public sector) holds, with repeat tenderers being completely invisible for the purposes of automation so long as they are not awarded contracts.
All of this leads me to think that there is a big blind spot in the current EU approach to open procurement data as the solution/enabler of automatisation in the context of EU public procurement practice. In fact, most of the crucial (back office) functions — and especially those relating to probity and quality screenings relating to tenderers — will not be susceptible of automation until (or rather unless) different databases are created and advanced mechanisms of interconnection of national databases are created at EU level. And creating those databases will be difficult (or simply not happen in practice) for as long as the ESPD is in place, unless a parallel system of registration (based on the once only principle) is developed for the purposes of registering onto and using eProcurement platforms (which seems to also raise some issues).
So, all in all, it would seem that more than ever we need to concentrate on the baby step of creating a suitable data architecture if we want to reap the benefits of AI (and robotic process automation in particular) any time soon. As other jurisdictions are starting to move (or crawl, to keep with the metaphor), we should not be wasting our time.