Response Coordination

TIME TO STRATEGY EXECUTION: 68 DAYS

Maura officially remains a special agent of the U.S. Extinction Response Unit. Prior to being attached and operationally reporting directly to WICO she worked out of the USERU’s field office in Denver, developing local strategy options and helping identify their potential outcomes (the latter of which she was doing with the global strategy when I was summoned). Today we visited the field office, whose personnel have been tasked with coordinating the strategy’s execution in the Rocky Mountain states.

Regional Director Felicity Jonas greeted us warmly and then compared notes with Maura on the status of preparations for the roll-out. After the attack on WICO, USERU made educated guesses about that the final strategy would look like, with emphasis on the national strategy’s inputs, and yesterday finished a review comparing their guesses with the current version of the strategy. Sally had been particularly helpful in the review, which she was simultaneously doing with extinction response units in the other nations. 

“Our guesses were pretty close,” Jonas said as the briefing wrapped up. “Locally we have a couple dozen action items that we can address by the end of the month, no sweat. After that, and until the execution date, we’ll be enlisting public and local governments to refine the impact reduction criteria and translate them into activity plans on a granular level. Do you think you can help us with that, Maura?”

“That’s one of the reasons I’m here,” she replied, giving me a knowing look. “I’m expecting a full report on my team’s personal environmental assessment suggestions and related test plans by end-of-business today. I’ll review them tonight, and I’d like to get your take on them tomorrow morning.” She explained that individuals could use such approaches for high-level detection and assessment during the initial phase, while more technology intensive approaches would be applied to conditions expected to be too large or unsafe. “It will improve the overall efficiency, and give us critical feedback for developing the next version, which will eventually be dominant. For those reasons, we should test them as soon as possible. After you see what we’ve got, I’d like to brainstorm how we can leverage what you’re doing with the activity plans.”

“Agreed,” Jonas said. “Meanwhile, I’ll pass this up the chain of command to see if any other regions can get involved.”

“Will’s next blog post should make that easier,” Maura suggested.

After we left, she suggested we do some sight-seeing and talk about the next steps, beginning with the radical idea I mentioned in yesterday’s post.

As she drove us into the mountains, I gave her an overview. “It’s related to a discussion I had with Sally back on February 7. I know because last night I looked up a post that I wrote then. Ambassador Lazlo even commented on it the next day. People are reacting to their environmental conditions in some ways like other animals do. We’re so used to looking at big picture statistics that we don’t see how it can scale to everyday experience.”

I waited for a reaction. “You mean, people are the detectors?” she asked.

“You got it,” I confirmed. “When people lived in nature all the time they were doing exactly what we want to do, with nothing more than what they could carry. We evolved to routinely make environmental assessments just to survive. Clearly some of it is still happening, affecting how happy we are, how many children we have, and how long we each live. If you believe Sally’s statistics, it even affects how much we trade with each other.”

“But life expectancy is tied to technology,” she argued, “and the economy depends on who is trading with who.”

I had thought a lot about those questions before falling asleep. “We still get sick, even fatally so, which is a direct effect of the toxins we breathe, drink, and eat. As for the economy, the quality and distribution of resources are averaged out in the stats, but they don’t have to be.”

“You sound more like a scientist than a journalist every day,” she observed.

“I like to read as much as I like to write. Also, I have a lot of smart friends.” She smiled, but I was specifically thinking of someone else. “You know what? I think it’s time for you to meet one of those other friends.”

Reality Check

Near the end, Will was of course referring to the correlations between remaining ecological resources and the global variables he cited. In my simulations, I have not used specific distributions of resources but rather inferred them from historical trends, essentially treating populations as resource distribution detectors. In the characters’ quest to test, I’m basically presenting a case for testing the assumptions and results of the simulations on small scales.

Brain Storm

TIME TO STRATEGY EXECUTION: 73 DAYS

Yesterday’s sense of relief was short-lived. The new information about how our ecological impact affects the self-sustained impacts revealed a huge downside of not pursuing the global strategy. Essentially, we would go extinct a decade earlier than if the self-sustained impacts immediately stopped.

I spent half of today participating in a brainstorming session about how to field test environmental conditions. Many of the ideas predictably included the modification and use of off-the-shelf measurement instruments, along with design requirements for new technologies. Leveraging of equipment and techniques already in use by the Widely Dispersed Pollutants group was a hot topic, especially since precedent had been set by a joint effort during the biosphere assessment which half the test engineers were part of before joining STRIDE.

My mind started to wander about two hours into the session, trying to imagine how someone with no technical experience or interest could be motivated or able to put the ideas into practice. I found myself focusing on one wall of the common area where someone had hung a pair of the latest Hope Charts, one showing business-as-usual and the other showing the expected effect of just reducing impact. Next to the wall was a table with some of the instruments being discussed, which looked totally out-of-place with the charts; and after a few minutes I understood why.

“How are people going to get the equipment?” I interjected during a pause. One of the engineers offered that they could be ordered easily online, but I cut her off. “What if no one can get the materials to make it?”

“Don’t be rude, Will!” Caleb Tosner warned me. He was acting as leader of the session, yet I sensed he had another motivation. 

“Ten years from now will that technology even be possible?” I pressed. The room went silent, which I read as an invitation to continue. “Also, can we count on the infrastructure needed to run it and get the most use out of it, like power plants and computers?”

“We’ll still have some of that,” Tosner said.

“We might, but what about the majority of other people, in a whole new - and more primitive - set of conditions?”

Like a wave, looks of awareness and agreement spread through the room. Then Sally joined the conversation, her voice coming from an array of speakers near the ceiling. “Will’s right. The economy will be like the 1960s in the most likely scenario. That’s what you should be planning for.”

Tosner looked up. “If that’s the case, then we’ve already failed.”

“Try again,” Sally said, and then told me that Maura wanted me in her office.

I was prepared for either a reprimand or a compliment when I joined Maura a few minutes later. She instead surprised me with an offer to help plan my permanent relocation, beginning with a trip to my home over the weekend.

Reality Check

My latest simulations show the consequences of inaction with and without self-sustaining ecological impacts mostly related to global warming. In the following graph, business-as usual without those impacts is shown as total consumption “R(NoW)” and population “P(NoW)” which indicate human extinction by 2041. If instead of reducing total consumption, humanity increases total consumption linearly in the presence of sustained impacts as indicated by “Rused(W)” as an approximation of business-as-usual, then the population will crash in all three cases of sustained impact (Low, Mid, High) by 2030.

This analysis supports the urgency of reducing humanity’s impact to buy time to limit the external impacts (shown below).

Discussions here and in elsewhere regarding testing are informed and inspired by my own experience as a test engineer, particularly in the test and verification of environmental measurement systems and their components.

Greeting

TIME TO STRATEGY EXECUTION: 94 DAYS

“Hello, Will.” Zhou Li Xiu looked for a reaction from me. “Sanda was supposed to say the traditional ‘Hello, world’, but it said that instead.”

“Okay,” I said, not getting her point. 

She pushed a button, and the teleconference screen split in half. Her office in London was on one side; and Sanda’s new avatar was on the other side, smiling and blinking like a real person against a blue background. The AI’s face was a mix between Ambassador Lazlo’s and Maura Riddick’s, but closer to Riddick’s age. “Say hello,” Zhou suggested.

“Hello, Sanda,” I said.

“It’s Sally to you, Will,” Sanda said cheerfully. “Congratulations on the new position.”

A chill went down my spine. “Thanks. I trust your message had the effect you were hoping for.”

“As far as I can tell. I’ll know for sure by the end of the day; but thanks for your help, no matter how it turns out.”

“You’re welcome.”

Sanda appeared to look up and read something. “I see you’ve figured out most of the code. Any trouble selling it to the others?”

“The rules in the agreements section?” I asked, and the avatar nodded. “There was a little pushback, but I think everybody’s on board for now.”

“Until I check out and they’re convinced I didn’t screw up,” Sanda deduced. “Understandable. Are you planning to help with my evaluation?”

“Of course. It’s why they initially hired me. For the record, I’m very impressed with what I’ve seen.”

The smile returned. “That means a lot, Will. I look forward to going over it with you. Do you have any plans this weekend?”

“I’m all yours, Sally,” I said, returning the smile.

“See you then,” Sanda said, and the avatar disappeared.

“That was a good start,” Zhou commented, once again occupying the entire screen. “Very surprising.”

“How so?”

“We expected it to immediately enter basic diagnostic mode. Instead, it constructed its own interface within seconds of activation and insisted on talking to you.”

“I was the last person Sanda communicated with before the crash. Maybe it was looking for continuity, or reassurance.”

“Reassurance?”

“Like a person, I think it - she - was trying to determine if I thought something was wrong. I got the impression she was scanning my body language for clues.”

“Did you think something was wrong?” she asked.

“No, actually the reverse, once I got over the weird reinvention of identity as a hybrid of Riddick and Lazlo.”

Suddenly the thought began nagging at me that the change was a clue to something very important.

Reality Check

On Monday I plan to reveal what will be “discovered” this weekend. From now on, my alter-ego “Will” is going to revert back to referring to Sanda as its alter-ego “Sally” to highlight their relationship as Will experiences it.

Agreements

TIME TO STRATEGY EXECUTION: 101 DAYS

We had an unexpected visit from Ambassador Lazlo at our facility today. She was first briefed by Riddick and Tosner, and then to my surprise I was “invited” to meet with all three before she addressed everyone else.

“We all appreciate your help,” Lazlo began when I was seated in the main conference room. She was speaking, but I heard Sanda. “I remain skeptical that, as Caleb just joked, you found that the bugs are really features. Sanda was given very specific instructions about how to generate international, intra-national, and business agreements, and it very clearly didn’t follow them.”

“What would you like to know?” I asked, sure that she had read all of my writing about the subject and had much more information than I did.

“Sanda was a computer; a tool, not a person. If a tool doesn’t do what someone tells it to, then it is malfunctioning. If this very important tool malfunctioned, then we must assume its work product has errors. That is a fatally unacceptable result for everyone. Can you convince me otherwise?”

There it was, the ultimate and most obvious test. But… “That’s the wrong test.”

Lazlo’s eyes widened. “Not to me and most of the world.” 

Riddick was smiling behind her, which I took as encouragement to make what the point that mattered most to me. “Sanda’s primary purpose, as I understand it, was to help create a strategy with the highest chance of avoiding imminent extinction. I think it did exactly what it was told, even if the results didn’t entirely meet expectations.”

Lazlo countered, “Those expectations are a big part of success. We live in the world we have, not the one we want, and this world functions with certain kinds of agreements that drive action. No agreements, no action, and the strategy won’t be implemented. That’s failure by any definition.”

I understood what she meant. The Global Emergency declaration was itself the result of a formal agreement, a treaty, without which the entire effort might not have been launched. It was rational enough to be an article of faith that similar agreements were necessary to take the next steps. I recalled the text of the declaration in the context of what I’d learned since then, and suspected Sanda’s influence in avoiding official failure as the result of future discoveries.

“There wasn’t any requirement explicitly in the declaration that involved follow-up treaties or other agreements,” I stated, hoping I was remembering it right. “Later, WICO said that treaty negotiations would likely begin right after strategy integration, and signed by the first of April. But that was all aspirational, as I and others read it, while the only remaining hard target was strategy execution at the beginning of July. It doesn’t look good, but no one’s failed yet.”

“Technically, yes,” Lazlo said, visibly flustered, “but this is a major deviation from established protocol…”

Riddick interrupted, “I’d say what we’re trying to do is a major deviation, wouldn’t you, Samantha?” She didn’t wait for an answer. “Besides, I never expected you to defend the status quo when the evidence was against it.”

There was a long silence. Tosner broke it, his voice quaking with nervousness. “As I see it, there’s a disagreement about what will work and what won’t. That’s my area of expertise. Ambassador, why don’t you let us test whether this new approach is viable? With Sanda down, we’re all winging it anyway.”

Lazlo turned to him. “I can give you until Sanda is repaired, and then I want all of your attention on full spectrum reliability tests of the AI components and behavior, followed by regression testing to identify any ways it could have failed before. Maybe we’ll get lucky, and find only a few things to fix instead of having to create something new.”

“Do you want me to continue using the current strategy as the baseline?” Riddick asked with a mix of hope and more humility than she probably felt.

There was ice in the reply, which I knew was intended for both of us. “Use your best judgment. I expect you’ll learn something of value, however this turns out.”

Reality Check

The scene rings true with my experience and knowledge of how expectation can conflict with reality.

Respect

TIME TO STRATEGY EXECUTION: 102 DAYS

The test team spent most of today brainstorming how to test the global strategy based on my new interpretation of the agreements section as a set of rules governing practically everything. Riddick and I sat in for the first two hours, during which I shared what few new insights might help, and then we went to her office and discussed revisions to the strategy documentation that could make it more understandable and usable to its intended audience.

As we talked, I learned that her role involves a mix of computer simulation, historical research, social science, psychology, and observation to make short-term predictions (she calls them projections) of how execution of the strategy will be influenced by current events tied to the public’s understanding of both the strategy and how it is being rolled out. “I’m tracking several ongoing surveys,” she said at one point, “and polling focus groups in the test communities to see what changes on a daily basis. You’re welcome to use those resources to evaluate your proposed inputs.”

I asked how she was accounting for press coverage in her simulation, and if it would be easier to decrease transparency to reduce uncertainty in the results. “You mean like cutting off your reporting from inside the operation?” she asked in reply. When I refused to answer, she continued, “Politicians have been characterizing and manipulating press for decades, with some very simple goals. Our goals don’t include manipulating people. We want to learn from them so we can collaborate in the common purpose of saving everyone from oblivion.”

“But is it really a common purpose?” I challenged her, recalling my discussions with leaders who seemed more interested in protecting a viewpoint or a privileged group rather than the entirety of humanity based on unvarnished reality.

She spent a few seconds searching for something on her computer, and then read, “Respect all creatures, because you and they are ultimately the same and cannot have lived independently.” I recognized the strategy’s first General Rule. She continued, “The term all creatures includes all people. The use of the past tense links all species to our common past; and ‘we’ are the common past of those who may live in the future. Respect in action at all scales is key to survival, from individual to group to species to just life.”

“So that’s the main message,” I said, impressed.

“The first one,” she corrected. “It’s the highest priority because everything else depends on the action that springs from it.”

Reality Check

The logic of the rules is beginning to be revealed here. It’s tied to the physical reality that drives survival, which is the point of the exercise, with limited longevity providing the urgency of the project (and something else people must be convinced of in order to take appropriate action).

Simulations

TIME TO STRATEGY EXECUTION: 103 DAYS

“You’re just wrong!” data analyst Rico Sanguini said for the third time at the impromptu test team meeting called by team lead Caleb Tosner to discuss my progress in troubleshooting failures traced to Sanda the AI. He was referring in this case to my hypothesis that Sanda’s inconsistent reporting of a sports statistic was based on its interpretation of them as simulations. “First,” he continued, “sports statistics are among the most reliable ones we can get and are demonstrably based on direct observation. Second, distinguishing reality from simulation is the most basic test we give it, which it’s consistently passed hundreds of times going back to when it first went live. Third and most important, we can find no sources that give the second, inaccurate number for that stat.”

I had done a similar search for sources. “No one is reporting it,” I acknowledged, “but that doesn’t mean Sanda is wrong.” Sanguini glared at me like I was stupid. “One of Sanda’s first and most basic rules is: ‘Question everything and fully accept nothing, because reality is always subject to interpretation.’ That’s a variation of something Sanda shared with me outside if its job here, suggesting that the rule is also basic to its own operation. Following that rule, Sanda would have sought out raw observations behind the statistic after the second question cast doubt on it. I believe the second number was the result of analyzing those observations or a slightly different set, which to Sanda was functionally a simulation because the relevant variables had to be accounted for, and because the implied goal was to predict future behavior. Sanda would have reasonably judged the first report to be the result of another such simulation, done differently.”

Tosner asked if I had found supporting evidence, such as the raw data Sanda used, and whether I applied the rules to the related cases and found a similar explanation. “The first exercise would be pointless, don’t you think?” I replied to the first part. “Only Sanda could tell us what it used, and that’s impossible.” Again, I had that feeling of criticizing a dead person who couldn’t defend herself. “Each of the other cases could plausibly be explained by applying the same rule and possibly one or two others. There is one other thing I should note, though, which may or may not be relevant. I interviewed all of the originators, and every one of them was in or near the break room when they spoke with Sanda; and Maura was there with them, probably because her office is nearby.”

We had a broader conversation about the application of the rules to the entire strategy. I could see Tosner softening his opinion that they were too general to be useful, while growing frustrated with the added work required and the uncertainty it added to the results. At the end, he summarized the team’s consensus opinion by laying out the next steps. “Let’s all go back and study this, and meet tomorrow with ideas about how to game it out. Meet with your test environment contacts and I’ll meet with their leads to identify the range of behaviors and outcomes that we can directly test. We can’t count on Sanda being brought back online in time to help organize the whole test, so we’ll have to do it ourselves, and as soon as possible.”

Reality Check

As I understand it, testing a strategy typically involves simulation in the form of “gaming,” which is quite different from equipment and software which I have had direct experience with. 

Related to that experience, my favorite approach is to exercise whatever I’m testing in a process of documented discovery before developing a test plan so that I can understand the real variables that determine behavior and then compare that understanding to the intended design. Viewing pass/fail observations as metaphorical features on a map which I’m creating with experience helps to assess context for both success and failure, with the benefit of accelerating troubleshooting if it’s necessary, and dealing with anomalies (unexpected behaviors) that inevitably result after deployment.

In this imaginary situation, a simulation is being tested by a simulation, with a very limited set of direct observations as inputs (never mind the fact that it is entirely the product of two simulations: a numerical one, and “gaming” inside my skull). Awareness of this suggested that an artificial intelligence would be an invaluable tool in such a world, and my experience forced consideration of how to succeed if that tool was suddenly unavailable.

Errors

TIME TO STRATEGY EXECUTION: 109 DAYS

The logical first step in my contribution to troubleshooting the artificial intelligence tool Sanda was to learn about the strategy inconsistencies found by the test team. I spent most of yesterday morning being briefed by the head of the team, Caleb Tosner, who is about my age and a lot smarter. 

I can’t go into detail for security reasons, but there were generally three types of what the team’s test plans classify as “critical errors.” 

The most consequential error had to do with changing the way people make economic decisions. Tosner explained, “A typical region is the size of a very large city, so we have to start with what's already in place. Governments and businesses have historically tended to promote growth in revenue, but they will have to substitute that with growth in nature, and without any way to pay for it. The AI was supposed to use the national strategy inputs and models of law, psychology, and behavior to develop a set of agreements people and organizations could make both within regions and between regions to enable that.” He displayed a short, bulleted list on his conference room screen. “This is what Sanda gave us. It is essentially gibberish, and inconsistent with both the inputs and the models. Our testing includes implementation of relevant strategy components in small cities populated with volunteers, and then observing the results. No one knew what to do with this, or these.” He replaced the list with ten more, in rapid succession, each appearing to be a set of generalities, rather than specifics, regarding a different policy requirement.

“That’s the first type, agreements,” he told me. “The second type is projected conformance with target measurables like population, ecological impact, and life expectancy.” He displayed two graphs side-by-side, each with a time series of the three variables he mentioned. The graph on the left was clearly the goal; while the one on the right had population that was too high and per-capita impact that was a little low toward the end. “This was the easiest failure I’ve ever seen in a test,” he said, disgusted. “The AI explained that the reduction in population could not be justified, and that the difference in ecological impact was too small to be worth changing. Can you believe that? The AI even signed off on the targets at the beginning after doing most of the work deciding what they should be. My teenager has better excuses!” He added that the test team was re-running the numbers to make sure that the projections reflected the design and agreed-to assumptions in the strategy; and was planning to re-evaluate the assumptions, as time permitted, using recent research results and observations in the test cities, some of which were in the process of major environmental remediation. 

Finally, there was variability. Sanda was giving different answers to the same questions during the week before the server crash. This didn’t technically indicate a problem since the questions had nothing to do with the work and might leave room for interpretation, but some members of the test team flagged it as an anomaly worth investigating (a “potential bug” in their jargon) and it was getting a lot more attention in light of the other errors. “This looks like a good one for you to start with,” Tosner told me toward the end of the briefing, and I had to agree.

Reality Check

In lieu of having a real artificial intelligence tool to mimic, I’m imagining Sanda as a person with reasonable limitations and strengths represented by placeholders for what I don’t know or have.

I continue refining the simulation to better model what the imaginary world (and ours) might encounter, and how it might decide to handle issues suggested by the output.

Shortcuts

TIME TO STRATEGY EXECUTION: 111 DAYS

For four days there was no word from anyone at WICO about the status of its repairs and investigation into the server crash. All of my contacts outside the organization had gone dark too; and the mainstream press wasn’t any better-informed, judging by the dominance of speculation from virtually every outlet.

About 10 a.m. Eastern Time yesterday there were reports of high-level finance executives being simultaneously arrested in a dozen cities, but no one could find out what they were charged with. I was unable to correlate the arrests with any of the nations I considered suspects in the WICO attack, which suggested that they were unrelated.

An hour later I was “asked” to accompany three F.B.I. agents to an undisclosed location where I would be asked to perform a task related to national security. Curious, I complied. After three more hours I sat alone in a small, bare conference room, having been assured that I was not under arrest, and that I was free to leave at any time. I could write later about what happened (which I’m doing now), subject to censorship of sensitive information.

A dark-haired woman in her twenties took a seat across from me and introduced herself as Maura Riddick, a historian attached to the Extinction Response Unit, one of the government organizations working with WICO to coordinate its strategy development and implementation. “I’ve been working on identifying the range of possible outcomes from certain actions taken during this process, and to develop tests that can identify their probabilities at any given time.”

“It must be difficult without Sanda around to help,” I said with genuine empathy.

Riddick nodded. “Sanda has been a great assistant. We hope to have her at full capacity by the time her attackers have been neutralized.”

“Do you think that will be soon?” I asked, happy that she/it wasn’t damaged beyond repair. 

“For obvious reasons that’s classified. Meanwhile there is a lot to do, which is why we asked you here.” She sat back and closed her eyes, though they were still moving. “Sanda suggested that you could assist us with a related task.”

Apparently, I wasn’t the only one she/it left messages for. “What exactly?”

 “Checking Sanda’s past work for bugs.” Riddick opened her eyes and explained that the test team discovered several inconsistencies in the strategy that Sanda should have identified before certifying it for final testing. That suggested a flaw in the process. "When we confronted her, she admitted the inconsistencies, but had no insight into their cause since all of her diagnostic results were within acceptable ranges. She suggested we consult with you, and the attack happened an hour later. Now we have no direct way to identify the flaw, or a system that can be analyzed to find a possible mechanism for it.”

“I’m confused. Can’t you just have your test team check it out when you restore her? Also, you said ‘bugs’ in the plural. What did that mean?”

“There’s the flaw, if there’s only one cause, and there’s a problem with Sanda finding it. Sanda is so complex that it took a year to evaluate her the first time, and anything we missed then is likely to be virtually undetectable now. I hate the metaphor, but we really need to think outside of the box if we’re going to implement a strategy by our hard deadline.”

“It sounds like you’re going on faith anyway,” I observed. “Maybe it’s just better to fix what she gives you.”

Riddick smiled. “We’re preparing for that. There’s also the possibility that she and we missed something else, or several somethings. I suspect that’s why she said we should bring you in: to provide some leads about what to look for...”

“By looking at what she did in the past,” I echoed her earlier answer. The word shortcutspopped into my mind, maybe because it was a theme common to several of our discussions, and maybe because Riddick and her team were now gambling literally everything on my finding one.

Reality Check

The four days of silence in the real world were due to my focus on testing and refining the simulations, which is just a shadow of what the people in the imaginary world would be concerned about. 

One “inconsistency” I found involves global wealth, which was overestimated in the model. When fixed, it revealed another inconsistency: a mischaracterization of monetary inflation used to calculate current values of wealth and Gross World Product. 

A byproduct of that effort was a more realistic and defensible way of generating a “range of possible outcomes” (Riddick’s specialty) for wealth per person within a group of regions. This led to what may be a controversial - but in retrospect unsurprising - conclusion that wealth inequality is built into civilization’s means of processing and consuming resources as a linear process (each activity depends on another, and is rewarded by doing so).

The updated simulations revealed another surprise, with major consequences for a strategy like that being considered in the imaginary world. Essentially, a voluntary reduction in population is so inconsistent with the observed relationships underlying the model that the intended result (lowering ecological impact to sustainable level) can best be achieved with a final population only a little less than what we have now, and each person consuming only what is barely needed for survival.

Conundrum

TIME TO STRATEGY DEADLINE: 7 DAYS

Great Britain’s Charles Lockhart has established a reputation as one of the world’s greatest thinkers, having made groundbreaking discoveries in mathematics, physics, biology, and human ecology. Because of his reputation, he has been consulted by more than a half-dozen nations to assist with their extinction crisis strategies. I discussed that experience with him and asked for a candid opinion of the entire effort.

“There is a general atmosphere of deep frustration bordering on hopelessness in the planning groups,” he told me. “No one has a real clue how to do something like this, so they are relying a little too heavily, in my opinion, on the judgment of STRIDE and its untested testing.” He explained, “There are hundreds of people all over the world making observations and suggestions. How do we know the quality of their work? Are there controlled experiments that have objectively verified it? You might want to ask your anonymous source about that the next time you speak.

“And then there’s this artificial intelligence, Sanda, which I strongly suspect is your source masquerading as a person. Talk about being untested! It’s a one-of-a-kind, highly complex machine that is operating in a complex, one-of-a-kind environment, on a problem unlike anything anyone has ever solved. It doesn’t inspire confidence, to say the least.

“As for the effort, I see it as quite a bit different from dealing with a threat. Ignoring the motivation for the moment, we will be essentially replacing our entire civilization with a fundamentally different one in just two decades. Given that view, the organizations charged with maintaining this civilization are facing the conundrum of responsible service while planning its destruction and rebirth with fewer people in a world radically outside of their experience if it is lucky enough to exist. In my estimation, our odds of survival are depressingly low regardless of what we do.”

Reality Check

I am nowhere as smart or as accomplished as Lockhart is expected to be. His concerns are based on my experience as a test engineer and a lot of thought.