Make Rapid Decisions

Welcome to Star Compass!

What’s inside this week:

🧑‍🚀 This Week’s Mission: How do you avoid analysis paralysis?

🌌 This Week in Space: Three things you may have missed this week.

🚀 Ask a Rocket Scientist: How do we constrain Artificial Intelligence?

🔭 Next Step: Take a position.

With so many analysis tools and computing power at your disposal, it is natural as an engineer to want to explore options in as many ways as possible before deciding.

We teach engineers many methods to analyze a problem, but few methods to decide on which answer to choose when.

But in today’s fast-moving environment, indecision can have as significant an impact as making the wrong decision.

I have worked on several projects beset with challenges from analysis paralysis, the impact of indecision, and how to make decisions faster. I wish I had the OODA Loop to avoid learning these lessons the hard way.

The OODA Loop is a framework for making decisions in fast-moving, high-stress situations. OODA stands for:

This is often shown as a simple continuous improvement loop.

But the original idea proposed by Air Force Colonel John Boyd in the 1970s is more elaborate, with more options for iteration. The key difference in Boyd’s more complex loop is that multiple feedback loops show that you may transition backwards to the beginning when more observation and orienting is necessary before deciding or acting.

Boyd continued to refine the OODA loop until he died in 1997. This is shown in this figure adapted from his 1996 publication.

Boyd also believed Orientation is the key to this process. It involves all aspects in a decision-making environment, including analysis, synthesis, previous experience, and psychophysical ability, as well as new information as you iterate back to it. Orientation is not just about the physical environment, but also moral and mental dimensions. Orientation is the cognitive engine where decision options are formulated.

To understand this further, it is important to go back to the historical origin of the OODA loop. Colonel Boyd originally developed his ideas while trying to understand why US F-86 fighter pilots fared well against technically superior MiG fighters in the Korean War.

He attributed it to the fact that the F-86 planes had a wider field of view than the MiG planes and that the F-86 hydraulic controls enabled faster transitions between maneuvers. Both plane characteristics enabled the US pilots to make broad observations, orient themselves to varying uncertainty, decide on a response, and act quickly to gain a combat advantage.

Artificial Intelligence now allows OODA loops to be executed more quickly to make split-second decisions. This is important with new military threats like drones and hypersonic weapons.

The military applications set the stage for using the OODA loop more broadly than air combat. For all kinds of project management, an OODA loop allows teams to adjust their plans to changing circumstances by cycling through the iterative decision-making process.

In space operations, the OODA loop is often used for satellite defense and on-orbit autonomy. For example, the four stages in a space context look like this:

The key to applying this in any engineering situation is to move beyond just the Observe and Orient stages to offer actions to be taken through Decide and Act. Provide leadership with a recommendation based on the data and analysis you have so far, and then together decide if you need to go back in the OODA loop for more before deciding to act.

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📡 OPPORTUNITY: They say you shouldn’t chase titles. This title is an exception.

The Planetary Guardians are hiring a Chief Planetary Officer.

They are seeking an exceptional leader to guide their next phase of growth and help turn Planetary Boundaries science into an actionable framework for governments, markets and civil society. In this role, you will work alongside their global collective of Guardians, leading climate scientists at the Potsdam Institute for Climate Impact Research, and an ambitious network of partners.

This sounds more like an opportunity to be a superhero, but learn more details about this unique position here: https://lnkd.in/ewA2i9-N

📚RESOURCE: Aerospace is a niche in the tech world. But there are niches within niches.

Planetary science is one of those.

You probably won’t find planetary science jobs on LinkedIn, but you will on this site:

https://lnkd.in/eaesDm8v

Anyone can add an announcement to this site for free, and the site is free to consult without logging in.

It is only fitting that this was shared by a friend with an even deeper niche title.

Thanks, Astrobiologist Michaela Musilova, for sharing.

🌎 COMMUNITY: It was clear when this post last week went viral that we are building a community. This post resulted in 16,431 impressions, with 86% of those coming from outside my network. It is a new way to address the anticipated shortage of 1 million engineers in aerospace by 2030.

It is the Making Space Ascend Aerospace fellowship program designed for disabled jobseekers and veterans to expand the pool of skilled workers. We are starting in Colorado but are looking to expand to other states in the future.

I am fortunate to be an advisor.

Applications are due Nov 8th.

Learn more here: https://lnkd.in/eK9smwkX

How do we constrain Artificial Intelligence?

- A question I have had lately

Sometimes science fiction offers answers.

In 1942, Isaac Asimov first introduced his Three Laws of Robotics in his short story “Runaround.” They are:

First Law: A robot may not injure a human being or, through inaction, allow a human being to come to harm.

Second Law: A robot must obey orders given it by human beings except where such orders would conflict with the First Law.

Third Law: A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

These three fictional laws have shaped real-world robotics ethics for decades. Since Artificial Intelligence (AI) can be considered an extension of robotics, some technologists have considered Asimov’s laws as a potential AI safeguard framework.

Last year, Dariusz Jemielniak proposed that Asimov’s Laws need an update. Due to AI’s ability to go beyond Asimov’s original concerns about physical harm and obedience, he proposed a Fourth Law.

Fourth Law: A robot or AI must not deceive a human being by impersonating a human being.

As a result of implementing this Fourth Law, the following would result:

While proposed watermarking of AI content is a start, this Fourth Law implementation needs more work. The University of Colorado has been providing resources to improve AI literacy, as have other educational institutions.

But to address social trust, more safeguards are needed. Maybe Asimov’s Laws, and other proposed amendments like Jemielniak’s, will get us there.

With the speed AI is moving at today, we must make decisions quickly about how to balance exploring the technology untethered while maintaining trust and safety.

Thanks to my friend Aroh Barjatya’s LinkedIn post that inspired me to explore this further.

Got a question about navigating your aerospace career? Reply and ask. I’ll answer the best ones right here.

This week’s newsletter provided a pilot-inspired framework for making decisions faster.

The key when presenting suggested decisions to leadership is to take a position. Options are great, but what is recommended?

The more you make recommendations, the more you build trust that you can make those decisions yourself as a future leader.

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