What can the search for extra-terrestrial intelligence tell us about the state of our democracy?

Fermi’s Paradox and the Drake Equation may help us answer the most urgent question of our time.

I would love to discover that the universe is teeming with alien life. And someday, despite the odds, we will meet “them”. As a species, we have pondered this question for at least 100 years. The most famous examples of thinking about “life out there” are Fermi’s Paradox and the Drake Equation. But what possible relevance could these have to understanding the state of democracy? In this article I will attempt to answer that question. This will involve equations, but trust me, they won’t be scary.

Fermi’s Paradox and the Drake Equation

In 1950 Enrico Fermi posed his now famous paradox, when he asked “where is everybody?” This was in response to there being billions of stars in the galaxy, each with many planets. And a fraction of them might support life. The question is “what fraction”?

In 1961, the astronomer Frank Drake created a framework to help answer this question. He presented it at the first scientific meeting on the “Search for Extra-Terrestrial Intelligence” (SETI). His now famous Drake Equation looks like this:

R = R_* ⤬ f_p ⤬ n_e ⤬ f_l ⤬ f_{i ⤬} f_c ⤬ L

This is not an empirical formula derived from first principles. It predicts the number of civilisations in the Milky Way. It does this by breaking down one unknown into a set of smaller ones. We can measure, estimate and debate the parameters on the right-hand side. For example, f_p is the fraction of stars that may have planets. This equation gives rise to estimates ranging from zero to millions.

This brings me onto the question posed in the title “What does this have to do with UK democracy?”

My answer is to propose the Democracy Equation to assess intelligence in parliament as a proxy for good policy making and a healthy democracy.

The Democracy Equation

This is my Drake-style equation to determine a Capability Index for our MPs:

CI = (R_e + R_p+ R_m + R_l + R_t + R_c ) / 6

Each parameter is a capability ratio describing the following capabilities:

R_e = Education

R_p = Professional experience

R_m = Military experience

R_l = Life experience

R_t = Public trust

R_c = Communication skills

Each R value is a ratio of assumed capability over desired capability:

R = assumed / desired

We combine them to calculate an average capability index. The best way to appreciate this is to go through an example. To begin, we will consider each parameter in turn.

Education

The first capability relates to education. I had difficulty finding an official, up-to-date figure for this parameter. There are some credible data from a 2015 Campaign for Science and Engineering study. This data includes medical degrees as well as STEM subjects. These are subjects in science, technology, engineering and mathematics. The study provides an estimate of 95 MPs (15%).

For our desired education target, I propose that we should have 70% of MPs with a strong education in STEM subjects. This gives us the following capability ratio:

R_e = 0.15 / 0.7 = 0.21

This scale of STEM education is vital to building a modern technological economy.

Professional Experience

Here we are looking for significant experience starting and running businesses. According to an Industry and Parliamentary Trust report, 20-30% of MPs come from business or commerce backgrounds. Only a few dozen are likely to have been responsible for a large number of employees. So let’s assume there are 50 MPs in this category, or about 8%. I would not argue, though, if you felt this is too high.

It is unrealistic to expect much higher than this, so I will set a desired target of 16%, giving us a ratio of:

R_p = 0.08 / 0.16 = 0.48

Military Experience

According to the same report, there were only 4 MPs (0.61%) with a military background! I find this incredible, and also a challenging one to think of a sensible target. We have been underspending on our military for many years. Our treatment of veterans is shocking. It is obvious that only 4 MPs with military experience is not working and we need to boost the proportion. That said, I don’t think we should be on a permanent war footing, so I propose increasing to 5%(32 MPs), giving us:

R_m = 0.062 / 0.05 = 0.12

Life Experience

For life experience, I am interested in which MPs have worked in real, demanding jobs. For example: mining, fishing, building, caring, policing or farming.

It turns out that independent research and parliamentary data tells us a lot. And no surprises here. Experience in traditional working-class, or labour-intensive jobs, is rare among MPs. According to a study by the Institute for Public Policy Research (IPPR), only about 7% of MPs come from a working-class background. So 45 in total.

A UK Parliament paper “Representatives of Society” backs this up. This suggests the number is less than 10%. For example, in 1945 there were 45 ex-miners in the Labour party. This came down to 6 in 2010.

This deficit undermines how parliament operates. So few MPs seem to grasp how their policies will impact their constituents. For example, would a farmer have supported an inheritance tax increase on farms? I will target a large minority of MPs, i.e., 195 or 30%. This gives us a life experience capability ratio of:

R_l = 0.07 / 0.3 = 0.23

Public trust

Assessing the number of MPs trusted by the public is difficult. I found a paper suggesting only 9% of the public trust politicians in general. Trust is not a direct proxy for honesty in politicians, but it is reasonable to equate the two. More honesty would engender more trust. 9% equates to 60 MPs. We could of course interpret this as 100% of MPs are honest 9% of the time!

With higher trust, parliament could better deliver policies. When people believe in what they are being told, they are more likely to agree. And this is most important for unpopular policies. At least that’s how I would like the world to work!

What do you think should be a realistic upper target? 100% is never going to happen, but imagine how things might change if we could trust most politicians. I am going to assume a stretch target of 80% of politicians, giving us a capability ratio of:

R_t = 0.09 / 0.8 = 0.12

Communication

I struggled to assess this parameter and AI did not help. Chat-GPT’s top example of a strong communicator was Keir Starmer! This is what AI sceptics refer to as an hallucination. Worse, it made no mention of Nigel Farage! Love him or hate him, he is one of the best communicators in politics today.

A good communicator is confident, passionate, knowledgeable, quick-thinking, and persuasive. Nigel Farage receives an almost perfect score on this basis. Poor old Sir Kier would struggle to get into my top 50%.

I am going to make an educated guess that at least 30% of MPs are good communicators, i.e. about 195 in total, and I am not expecting all MPs to compete with Nigel. But we should have at least 50% of MPs (325) with good communication skills. This gives us a communication capability ratio of:

R_c = 0.3 / 0.5 = 0.6

This is the highest capability index we have found and is not surprising. When standing for election, prospective MPs go through a rigorous selection process. Their communication skills are one of the key qualities assessed.

So what does this tell us?

Feeding this into the equation gives us the following average capability index:

CI = (0.21+0.48 + 0.12 + 0.23 + 0.12 + 0.60) / 6 ≈ 0.29

I had no idea what would fall out of this equation when I started. However, this result feels about right. I certainly would not have expected anything over 0.5.

In an ideal (but unrealistic world), each ratio would be at least 1. In theory, it is possible to overshoot. In practice, chance would be a fine thing!

In any case, I never claimed this would be the correct value. This type of analysis breaks down a large problem into manageable chunks. Then we can concentrate on each part in isolation. In effect, the answer is less important than the discussion and argument it gives rise to.

Another way to think about this result is that to tackle this low capability index, we don’t need to have 650 MPs. Our index applies to any number of MPs. I am not sure how many we should have, but often, less is more. Smaller teams tend to be more successful than large teams. If we tackle the identified deficits, a smaller team should do a better job!

The same argument would apply to the House of Lords. However, this involves more complex constitutional issues beyond the scope of this analysis.

Final thoughts

As I came to the end of this article, I remembered that Reform UK have proposed having unelected members in cabinet. This would include industry experts and leaders with vital skills and experience. My first reaction was negative. On reflection, this could be an excellent way to improve the capability index of the cabinet. This would also reduce need to make improvements across the House of Commons. There could be science behind this controversial policy!

The main short-coming in this approach is using older, unverified data and setting subjective targets. To address the data issue we could carry out a research project amongst current MPs. But we cannot avoid subjective targets. In my defence, my “democracy equation” does what Frank Drake intended in 1961. It provides a structured framework around which to have a sensible debate.

I will finish with a few questions:

1. Did you find assumptions realistic?

2. Have I missed any obvious capabilities, such as leadership for example? I found this one too hard to pin down and so relied on communication skills as a proxy.

3. What do you think about my preference for STEM subjects?

4. How does a need for more STEM education compete with the need for more life experience?

5. Is it worth weighting the relative importance of some capabilities?

6. Should we weight cabinet member capabilities higher than back bench MPs?

7. Did any of the results surprise you?