Extracted from Rules: Shaping Behavior and Knowledge, by Ronald G. Ross, 2023, 274 pp, https://www.brsolutions.com/rules-shaping-behavior-and-knowledge-book.html

Suppose you are training to be a host at a restaurant. You read or hear the following statement.

Customers need to be properly attired.

It's obviously important that you know this. The guidance is basic knowledge for the restaurant's community of people (workers, customers, etc.). It helps set the tone the restaurant wants to maintain.

But are you ready to go to work yet? No. "Properly attired" could mean anything from tuxedos and formal gowns, to bathing suits and bathrobes. You almost certainly don't know enough yet. The guidance is not yet ready to put into practice.

Let's be careful here. The guidance is not yet ready to put into practice if you want to be rule-based about it. Obviously, any guidance can be arbitrarily enforced (or not). So, let's assume you want to be fair and open about enforcement; in other words, you want a high degree of consistency and impartiality. (In society as a whole, this notion is called rule of law.)

What's needed for the guidance then? You need more to go by. The original statement needs to be interpreted into a more specific form. Perhaps that's how we arrive at a No-Shirt, No-Service rule for the restaurant. Much more concrete. Even that rule might not be sufficient for being rule-based in the sense we mean. You probably also need some What's-a-Shirt rule(s).

And there are other questions you should ask. Is the intent of the rule to disallow service, but not entry? Perhaps the true intent is no-shirt-no-entry.

This drill-down from high-level guidance to rules specific enough to be put into practice is a central requirement of rules for groups and communities of people. Retaining memory of these drill-downs (traceability) is, in turn, a key area that platforms should support.

Another Example

Suppose someone in authority states:

Safety is our first concern.

They've obviously said something quite important. It doesn't really matter whether they call it a policy, principle, doctrine, goal, or whatever. It provides high-level guidance and helps establish priorities. It's a key bit of knowledge.

But does the statement tell you exactly what behavior is expected? No. It gives no specific criteria to go by — nothing to judge whether or not you are in compliance. What exactly counts? Any evaluation will be highly subjective — not rule-based in a meaningful way.

Now suppose someone in authority says:

A hard hat must be worn in a construction site.

Suppose they also give you adequate definitions and/or definitional rules for 'hard hat' and 'construction site'. Now could you act as an impartial judge in determining whether or not a particular worker is in compliance? You're certainly much closer now because you have an explicit criterion to judge by.

But wait. Did you notice that the statement does not say the hard hat must be worn on a person's head? Would it be acceptable to 'wear' the hard hat somehow buckled to the worker's belt? Actually, the rule currently doesn't even mention person or head. Are we to punish hard hats themselves for lying around not being worn?! Policy interpreters and rule analysts need to be careful readers, as well as highly imaginative in playing out different enforcement scenarios.

Am I being too picky? If you're a person in a construction site, and a brick happens to fall on your head, probably not(!). And if you're the company facing giant liability suits, probably not either. Here's a more complete version:

Revised Hard Hat Rule: Every person must wear a hard hat on their head while in a construction site.

There are always substantial risks in groups and communities of people. These risks often merit a high degree of completeness in expressing relevant rules.

The Gold Standard for Expressing Rules

There is no way to be rule-based about compliance, determinations, and counts unless rules are specific and definitive. Good rules avoid subjectivity and the impossible. They have been interpreted (drilled down) to a point that they can be used or applied directly. In other words, good rules are ready to put into practice. They are practicable.

Aside: If discretion is warranted in applying a rule, it should be exercised in full knowledge of the context and circumstances for which the rule was intended.

Here's the test for whether a rule is practicable:

A rule is practicable if any person who knows about the rule can observe a relevant situation (including his or her own behavior) and determine directly whether or not the rule is being complied with.

One important caveat: The person either needs to know the business vocabulary or have access to it (including all relevant definitional rules). Assuming that's the case, the person should be able to read any practicable statement and be able to fully understand it without external clarification. Creating practicable statements is a must wherever you can't depend on conversation for explanation — in other words, it's a must for all formal communication.

By the way, just because a statement sounds authoritative doesn't mean it's practicable. Consider the following example from one of our clients:

Statement: The product type, vaccine type, and manufacturer for vaccine dose must not be contradictory.

Sure. But what are the criteria to determine whether or not the product type, vaccine type, and manufacturer are contradictory for a vaccine dose?! The statement is obviously important, but it is merely a policy or a principle, not a practicable rule. Don't be fooled!

Achieving practicable rules in effect means squeezing out wiggle room. The 'squeezing' can be no small chore for policy interpreters and professional analysts.

Here's a possibly disturbing thought for you. Many software developers know far less about specific areas of regulation, business knowledge, and organizational priorities than policy makers and subject matter experts. Do you really want software developers making assumptions about the intent of 'un-squeezed' rules?!

No, better to have people in the know do that. Don't abdicate responsibility!

Wiggle Room and Automation

Squeezing out the wiggle room from rules is necessary no matter whether you automate a rule or not. In fact, it might be even more important if the rule is automated. Humans can apply common sense. Computers (as yet) cannot.

But that's not the end of the story with respect to automation and behavioral rules, in at least two respects.

• First, rule platforms absolutely need to be more accepting of natural language in expressing rules, if for no other reason than better governance.


• Second, AI and machine learning (ML) are rapidly changing the game with respect to detecting violations. Let me give you an example.
  
  For many years I used the hard-hat rule as an example of a rule that couldn't be automated. Then some years ago I started learning about automated facial recognition. I thought to myself, "Hmm, if a machine can recognize a face, surely it ought to be able to recognize whether or not someone is wearing a hard hat (on their head)."

I hope I learned my lesson. These days you can never be too sure about whether behavioral rules can be automated(!). For better or for worse, we're sure to see significant and ever-expanding opportunities to use bots in supporting behavioral rules.

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