How capturing if-then/else rules from Jersey's Charities Law in Excel (& in formal logic) is helping us to explore legislative drafting issues for "Rules as Code", particularly about human input and discretion. Picking legislation which does not involve calculating amounts of money (so not tax or social security), and trying to add no more than the minimum to what is actually in the legislation. Presentation on project for Jersey's Legislative drafting office, 28 Feb 2020, at Bank of England, joint event with UK Parly Counsel - knowledge sharing session on "Rules as Code" developments in UK & nearby jurisdictions.

1. Non-financial legislation:
human input, discretion & logic
Matthew Waddington, Senior Legislative Drafter, Jersey
Rules as Code Knowledge-Sharing Event, 28/2/20, Bank of England

2. Jersey – small, nimble
•Small team of drafters –
• close to policy-makers, who are also in small teams
• majority of drafters interested in Rules as Code, 3 with formal logic backgrounds
• active in Commonwealth Association of Legislative Counsel
•Small well-structured statute book –
• constantly consolidated on web
• organised into subjects, with (mostly) one Law per topic (eg just one Social Security Law)
•All-fibre broadband island –
• digital industry, supported by Digital Jersey
• “Sandbox Jersey”
• fintech & regtech
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3. Tunnelling towards techies from drafters’ end
•NZ, NSW (& Canada) – most of the running on RaC is currently from tech end
• we have looked to engage legislative drafters through Cwlth Assoc of Legislative Counsel
• we are also involving Jersey policy officers with grasp of reality of legislative process
•Most of RaC so far aimed at tax & social security
• as topics that lend themselves to calculation by computers
• also tech folk feel strange lure of older, badly drafted legislation in complex fields
• even outside of tax/socsec they are not using modern Cwlth drafting – eg “Beard Act 1934”
•We want to demonstrate benefits of RaC in non-financial legislation
• “fixing the plumbing” – boring improvements make a difference
• humans as “feature not bug” - human input as integral to law, not just a failure of coding
• legislation asks for human input - yes/no, innocent/guilty, reasonable/unreasonable, fit/unfit
• coding to capture complex logic which leads to right questions for human input
•Meanwhile our policy colleagues have started a trial on OpenFisca for socsec/tax
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4. Formal logic – to tease out issues
•We started with using formal logic to try to capture rules
from legislation -
•partly because it relates to computer logic, while also being
simpler & relating to drafting logic
• computers need “If …, then …, else …”
• we often draft without the “else” (if not)
• formal logic has → for “if, then”, without else
• so have to add an “if NOT-X, then” to cover “else”
•formal logic also has
• ↔ for “if & only if, then”, or
• ≡ for “implies”
•these tease out questions drafter might have missed (or
might sensibly want to leave unanswered) –
• is this the only case in which the Regulator may register?
• what is the legal effect if the person doesn’t qualify?
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5. Low tech – also to tease out issues
•No need go straight for scalable tech solution, if
just want demonstrate possibilities & work
through legal/drafting issues
•There is already software available -
• QnA Markup Editor
• or boring old Excel (thanks to BoE for tip)
•We are seeing what can be learnt from using
Excel’s IF, AND, OR, NOT functions to capture
rules from legislation
•We used our Charities Law – eg of “entity”
• Human has to answer yes/no (yellow drop-down) -
default to “unknown”
• Questions are faithful to text of legislation
• Computer “answers” (blue) – yes/no/unknown –
just if-then-else from human answers
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6. Issues from Excel minimalism so far
•Trying to capture only what this piece of legislation does - not coding more than is in it –
respect differences between law, fact & evidence
•Not trying to capture –
• other legislation (till it is coded in turn) – eg Companies Law, 1862 Associations Law
• case-law on interpretation – this is the one that tech folk focus on
• common (/customary) law concepts expressly used – eg unincorporated association
• underlying law (statutory or common/customary) – eg –
• criminal code or common law on mens rea for offences
• criminal procedure & sentencing legislation for consequences of offence
• admin law & human rights law on use of powers (& interpretation & validity of powers)
•But does seem to make sense to do some violence to text of legislation –
• cashing out definitions in same Law – eg “company”, “trust” from Art 1 into Art 2
• incorporate provisions from that Law’s subsidiary legislation – eg add Timing Order back into Law
• leave out meta-provisions – powers to make subsidiary legislation (just incorporate made subsidiaries)
• maybe incorporate Interpretation Law/Act principles & easy definitions – but not all? (“person”?)
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7. Discretion, definition & human input
•RaC is not about AI replacing human decisions & automating the whole law – but need avoid temptation
to say it is just about prescriptive/calculatable rules, not “discretionary” legislation
•“Discretion” is a loose term, and has degrees –
• “The Minister may, by Order, amend …” – classic discretion
• “The Regulator must, if satisfied that the applicant is a fit & proper person, …” or “Commissioner must
decide whether charity provides public benefit to a reasonable degree”
• “serve a notice requiring the recipient to act, within a reasonable time specified in the notice, to …”
•Application of rule to ascertained facts –
• any normal definition in words just requires a human to apply several words instead of one
• relatively rare for legislation to specify facts in terms of automated digital input (facts v evidence?)
• so there is human input almost inevitably when ascertaining facts (to see if rule applies)
•So coding non-financial legislation is then about coding the logic of the rules, to take us from one human
input point to the right next human input point. This is valuable in complex legislation – “fixing the
plumbing” by “cranking a logic handle”, instead of assuming only flashy AI magic is worthwhile.
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8. Human/digital input – Charities Law example
•Jersey’s Charities Law – charity status hinges on whether registered as a charity –
• Register is digital, so computer could check status without human input.
• But the Law still hinges on -
• whether entity is registered (fact),
• not whether the computer can currently confirm that (evidence).
•Definition of “entity” is built up from various other concepts, with varying degrees of
human judgement from (or potential for digital input), to answer “yes” or “no” –
• “company” – mainly defined as on register (which is digital) under Companies Law,
but also includes hold-overs from past Law (possibly not registered)
• “incorporated 1862 association” – not a digital register (maybe not even a register?)
• “trust” – “a trust over which the court has jurisdiction under Article 5 of the Trusts
(Jersey) Law 1984” – no full register, and that Law doesn’t fully codify trust case-law
• “unincorporated” body/association – not defined, no statute, relies on
common/customary law concepts
• foreign entity “substantially similar” to a category of Jersey entities – clearly a human
judgement call, even though it is in a definition without express provision about who
decides (so the court decides, if there is a dispute)
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