Category: Climate Crisis

Categories
Climate Crisis

A Transatlantic Take on Climate, Nudges, and that Extra Steak

When Decisions Get Hacked

  1. Introduction

Let’s focus on what unites us for a change, shall we? Climate change is a transatlantic headache – big, messy, and guaranteed to spark arguments at dinner parties. Europeans love a good regulation, preferably wrapped in a 300-page report and debated over espresso. Americans, on the other hand, prefer innovation and market-driven solutions, often with a side of “we’ll fix it with technology.” Yet, despite these cultural quirks, both sides wrestle with the same fundamental dilemma: How do we make real progress without torpedoing economies? How do we keep people on board without triggering social media outrage? And most importantly, how do we stop talking about solutions and actually implement them before Miami turns into Venice?

  1. Hacking Humanity, One Nudge at a Time

Our most crucial decisions – be it in courtrooms or at climate summits – are vulnerable to tiny, well-timed nudges. Dozens of studies reveal that small, almost imperceptible changes can alter opinions as swiftly as a viral tweet. A study on 1,112 parole decisions found that judges were dramatically more likely to grant parole after their coffee break and lunch – suggesting that even critical legal outcomes can be influenced by something as simple as hunger. If justice can be swayed by a sandwich break, what does that say about our ability to make sound decisions on something as complex as climate policy? Imagine a policy proposal on CO₂ pricing facing the same kind of arbitrary fate, its success dependent not on scientific merit but on the timing of the vote or the mood of the electorate. In both Europe and the U.S., this hackable nature of decision-making forces us to ask: are we really making informed choices, or are we just following the well-timed taps on our shoulders? And if so, how can we use this approach to get us where we need to be?

Here is a recent example from my own research: I noticed in a number of surveys with thousands of Americans and Europeans that whenever low-impact measures are presented alongside high-impact ones, the duds tend to dominate attention – regardless of their actual effectiveness. This cognitive trap dilutes focus and weakens outcomes. Therefore, the smart move is to leave the low-impact fluff off the menu entirely – because if it’s on the table, it steals the spotlight.

  1. A Side of Meat: Appetite, Underestimation, and Transatlantic Taste

One facet of our climate conundrum is that we sometimes just deny reality. My corresponding example comes served with a generous helping of irony – meat consumption. My surveys with more than 3,000 respondents indicate that both Americans and Germans dramatically underestimate how much meat we actually eat, but there is still a difference: Germans eat 77% more meat than they think, while Americans eat close to 50% more. In Europe, this underestimation might be a nod to a more measured approach, as if to say, “Yes, we consume, but we consume with restraint.” Across the Atlantic, however, the unspoken truth is that the U.S. may be feasting on burgers with an almost celebratory abandon. This disparity not only provides fodder for humorous banter at dinner parties but also highlights a deeper cultural divergence: while Europeans might engage in polite self-deprecation about portion sizes, Americans often have a robust, unapologetic appetite that spills over into their approach to policy and law.

  1. Facts, Figures, and the Illusion of Knowledge

One might think that more information equals better decisions, but it’s not the sheer volume of climate facts that matters – it’s understanding the effectiveness of the measures we propose. That is one of the key insights of a new multinational study with more than 40,000 respondents. Whether it’s a CO₂ price mechanism paired with transfer payments or a complex legal reform, the key lies in knowing what works. The study showed that there was only a limited difference between the U.S. and Europe regarding this point. Now take a second and consider the last pieces of information you saw on climate issues. My bet is that, most likely, you were fed facts on the climate crisis as opposed to explanations on effective policies. 

  1. Fairness: The Unwritten Law in Policy and Precedent

At the heart of effective policy – be it environmental or legal – is a deep-seated sense of fairness. Unfortunately, only about a third of respondents in high-income countries like the U.S. and Europe consider a carbon tax with cash transfers to be fair! The most important factor in all countries (surveyed in the study mentioned above) that encourages climate-friendly behavior adoption is “The well-off also changing their behavior”! So, even amidst ideological clashes, both Europe and America ultimately converge on the idea that a policy perceived as unjust is doomed from the start. Whether you’re drafting a judicial decision or a climate policy, fairness isn’t optional – it’s the foundation upon which trust and acceptance are built. However, this is just one aspect of what makes a climate policy effective.

  1. Cutting the Fluff: Focusing on What Truly Works

Imagine wading through 1,500 governmental climate measures only to find that a mere 63 are truly effective. That’s the arduous work done by a team of researchers led by the Potsdam Institute for Climate Impact Research, using an incredibly sophisticated machine-learning based approach. The takeaway here is strikingly clear: only very few policies were effective. In both legal and climate arenas, it’s about trimming away the excess and focusing on what works. Rather than indulging in an overload of well-intentioned but largely ineffective initiatives, both American and European policymakers could benefit from a more discerning approach. 

  1. Bundling: The Secret Sauce of Policy Success

According to the study, successful state actions often come in tailor-made bundles. Think of it as the policy equivalent of a perfectly crafted cocktail: each ingredient, from strict emission regulations to economic incentives, plays a crucial role in delivering a satisfying punch. Both, in Europe, as well as across the Atlantic, while there are certainly attempts at such integration, the process sometimes feels more like an improvisational jazz session than a rehearsed symphony. The lesson? Whether in law or climate policy, crafting a winning strategy is less about isolated acts and more about the harmony of a well-curated ensemble.

  1. The Transatlantic Tango: Differences and Similarities

The transatlantic divide resembles an elaborate dance, where each side steps to a different beat yet shares the same stage. The Europeans waltz through policy debates with meticulous precision and overengineering (Green Deal, CSRD, etc.). Their American counterparts, on the other hand, often prefer a more freestyle approach – bold, brash, and occasionally a tad chaotic. Despite these stylistic differences, both continents are united by a common thread: an unwavering commitment to addressing the climate crisis, even if the methods vary – and even if public perception is at times different.

  1. Reflections on Hackable Decisions and the Future of Policy

If there’s one thing to take away from this whirlwind tour of transatlantic policy, it’s that our most vital decisions are not immune to manipulation. Whether it’s the nuanced interplay of nudges in a judge’s decision-making process or the subtle persuasion embedded in climate communication, we are all, in some ways, victims of a hackable human nature. And yet, this vulnerability also presents an opportunity. By understanding the levers that drive behavior – be it fairness, effective communication, or the clever bundling of initiatives – we can design systems that not only mitigate the risks but also harness our collective potential for positive change.

Looking forward, the challenge for both European and American policymakers is to embrace these insights without losing sight of what makes their approaches unique. In either case, the goal remains the same: to turn our hackable human nature from a liability into a strength.

So, let’s stop serving climate side salads and start dishing out the main course. If Brussels obsesses over straws and Boston ignores heat pumps, we’re all just rearranging deck chairs – real progress demands focus on what cuts carbon at scale.

(This article was initially published in the Transatlantic Law Journal, Volume 3, Issue 4, p. 145ff. My thanks go to the editors for allowing me to post it here!)

Categories
Climate Crisis

Caution ⚠️ – Green nudges can backfire!

40% of ecommerce customers increase their return shipments when informed about the negative environmental consequences of product returns! 

This is what a team from the Universities of Frankfurt and Mannheim showed in a large-scale, randomized field experiment (published here by Marketing Science, a top peer-reviewed journal). This study really stands out due to its sample size (> 100k consumers!).

That ‘s the bad news (for a summary of nudges backfiring, check out this overview). But there is also good news:

  • 👍 The dual green nudge (example in the graph below) did not affect conversion rates and overall sales negatively. 
  • 👍 The researchers were able to effectively target the green nudges to the consumers most likely to react positively, using causal machine learning. 
  •  👍 Green nudging “seems to be particularly effective for consumers who would otherwise return at an above-average level”, as the authors put it.

Also, as the authors point out, the consumers where the nudges backfires may not be anti-sustainability monsters, but simply customers that are unintentionally reminded by the nudge that returns are possible. 

So, what’s the takeaway? If you’re going to nudge, nudge wisely! This study is a good reminder that not all green nudges are created equal—some might just nudge customers straight to the return label. But with a little finesse and some causal machine learning magic, you can turn those nudges into a win-win: happy customers and a happier planet. Let’s keep it green, but also keep it smart. 🌍✌️

Categories
Climate Crisis

Will the Robot Revolution Supercharge the Climate Crisis?

Will the Robot Revolution Supercharge the Climate Crisis?

After decades of robots acting more like clumsy toddlers, we’re now on the brink of a robotic revolution that could reshape our world by 2040, much like the steam engine once did—only with fewer coal stains. The prospect is both exhilarating and alarming. Picture a future where general-purpose humanoid robots handle household chores and work tirelessly in stores and factories, leaving us to kick back and watch Netflix. But hold on to your Roombas! With plummeting manufacturing costs, skyrocketing consumption, and the inevitable rise in emissions, the stakes are higher than ever. In this essay, I’ll explore how this impending wave of robots might not just transform our lives but also turbocharge the very issues threatening our planet.

In our household with three ladies, even simple appliances get names: Our robotic lawn mower, for example, is called “Matilda”. When nobody is watching, I like to sit down and just watch Matilda mow our lawn: It is a uniquely serene sight – until Matilda gets stuck again in our Rhododendron bushes. This is Moravec’s Paradox at work (“it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility”). Many of you probably use one or two of these household robots, and you have seen industrial robots in use, so you know: For more than 20 years, nothing much has changed in robotics: They only work in a very narrow, controlled environment. 

Yet, despite Matilda’s botanical misadventures, the Robot Revolution is gearing up to leap beyond our backyards. Buckle up, because this time, it’s different. REALLY different.

I believe we are on the cusp of a “RobotGPT” moment, similar to what happened in 2020 with the advent of GPT-3 (broadly accessible, of course, in November 2022 with ChatGPT). Here’s why:

We know that the AI revolution is powered by scale, i.e., by massively increasing the data used to train the model (the key benefit of the famous multi-head attention algorithm at the heart of the transformer architecture is to dramatically lower “training cost”, i.e., enable more data crunching). Scale has produced performance improvements (like “learning to learn”) most experts did not expect. Since the 1990s, the World Wide Web enabled the creation of readily-accessible, multi-modal data on an unprecedented scale. This is now fueling the AI revolution. So far, we have been lacking a similar source of data to train our robots the necessary “foundational manipulation skills” to operate in our messy real world. This is about to change!

Here are two paths to resolve this data scale bottleneck and kickstart the Robot Revolution: 

  1. Simulations: As I argued in a conference talk in 2019, significant progress will occur when computers can simulate their learning environments digitally. This is similar to the advancement seen with AlphaGo Zero, which became unbeatable at playing Go after just 3.5 days of simulation training, starting from zero prior knowledge. Not surprisingly, Nvidia’s robotics unit, led by Peter Fox, is pursuing this approach because it demands an even greater number of GPUs than current needs.
  2. Videos: Currently, training robots using videos—a method known as “pixel-to-torques”—has not been feasible on a large scale. Replicating complex real-world actions, such as cracking an egg, through “behavioral cloning” requires enormous amounts of sensory data to control the many actuators of a humanoid robot. Despite this challenge, researchers are making progress. If we can develop high-quality training policies linked to videos that systematically address these gaps, we might be able to use the vast amounts of existing videos (not just from platforms like YouTube or TikTok, but also from surveillance and personal footage) for effective behavioral cloning.

To me, both paths look equally promising at this point, and they may even be mutually reinforcing (because simulations on a massive scale could provide exactly the missing links between robot skill training and human videos). 

Just so you know – There might be an alternative approach to training robots for effective movement: developing learning algorithms inspired by the simpler brains of organisms like dragonflies or even worms. This method could reduce the need for large-scale data, such as that used in large language models (LLMs), at least for the movement aspects of robotics. 

Whatever approach we use to teach our robots to move like us, the designated “frontal cortex” is already there: Researchers have shown how the “open-world reasoning” delivered by LLMs can be used to steer robots if we combine them with robotic actions into vision-language-action models (VLAMs) and optimize them for end-to-end robotic control. 

So, most foundational elements for unleashing the Robot Revolution are either already available or really within our grasp (including, of course, hardware elements like better sensors, actuators, batteries, 5G connectivity etc.). That was not the case only five years ago. 

That’s why I am pretty confident with my following forecast:

Before the year 2040, I expect to see widespread use of general-purpose humanoid robots, both in commercial and private settings. I expect this to happen before we see fully self-driving cars (SAE Level 5). 

When this happens (as explained, in my view, it is no longer a question of “if”), this will trigger the biggest changes in our society since the invention of the steam engine! But let’s not boil the ocean, today I would like to hone in on the Robot Revolution’s implications for the climate crisis. 

First, I will list some individual trends that will be all but inevitable assuming my forecast unfolds as predicted. Then I will outline some key uncertainties.

Robot Revolution – key trends:

  1. Lower manufacturing costs: The most obvious implication of the Robot Revolution is that in a matter of just a few years, general-purpose humanoid robots will lower labor costs dramatically (RethinkX estimates labor costs of under $1 before 2035 and under $0.10 before 2045). 
  2. More consumption: The substantial decrease in manufacturing costs as well as the massive increase in 24/7 availability will increase general consumption (as it always has throughout human history).
    → Likely effect on greenhouse gas emissions: Strong increase 
  3. More near-shoring:  The Robot Revolution will drive a resurgence of local manufacturing in today’s high labor cost-countries. This will reduce transportation costs to some degree (but local transport will still be necessary).
    → Likely effect on greenhouse gas emissions: Limited decrease
  4. More free time: People rich enough to afford a humanoid robot will experience a massive increase in their free time since most household chores can now be outsourced to a general-purpose humanoid robot. This free time will most likely be invested in activities with a large CO2 impact (like weekend travel by aircraft).
    In addition, unemployed unskilled labor will also have more free time (though that effect is much smaller).
    → Likely effect on greenhouse gas emissions: Strong increase 
  5. More robots: Needless to say, all of this will massively increase the demand for humanoid robots which need to be manufactured, delivered, and maintained.
    → Likely effect on greenhouse gas emissions: Strong increase  

I am pretty confident with the certainty and impact of those six trends. However, there are a few uncertainties, and I am curious to hear your thoughts on them.

Robot Revolution – selected uncertainties:

  1. Fewer commutes? As many service tasks will be taken over by general-purpose humanoid robots, the need for humans to commute to work may be further reduced, if many of these tasks are completely eliminated.
    → Potential effect on greenhouse gas emissions: Moderate decrease
  2. Global South? If the Robot Revolution accelerates economic development in the Global South (and that is a very big ‘if’), this would increase per-capita emissions, but at the same time likely drive educational opportunities for women and thus further accelerate the decline in birth rates.
    → Potential effect on greenhouse gas emissions: Moderate increase

Let’s step back and see the forest for the trees: the picture that emerges is one of tremendous risk. If we are unable to decarbonize our consumption habits, especially our leisure activities, the Robot Revolution is likely to supercharge the climate crisis by substantially increasing greenhouse gas emissions. If you needed yet another wake-up call to keep fighting for rapid decarbonization of our economies, consider the Robot Revolution your ultimate call to action.

Categories
Climate Crisis

Change course! – Five bold hypotheses on climate communication

Not only since the German government’s energy-saving campaign (“Dear 80 million“) have we been swamped with well-intentioned advice on how to reduce our personal carbon footprint. Most of these checklists are wild collections of measures with dramatically different effects and questionable persuasiveness. At least that’s what I thought, so I set out to prove in a series of tests that simple adjustments could improve the impact of these lists. And in doing so, I came across a whole series of surprises…

In the following I would like to show that

  1. these checklists are currently a central dimension of climate communication,
  2. we climate activists can make them measurably more effective, and that
  3. systemic measures for frequent polluters can also be communication measures.

I will do this in the form of five catchy hypotheses, each of which I will then justify in detail and in an evidence-based manner.

1.   Steer climate communication away from the general climate crisis!

In a nutshell: The question is where best to deploy our scarce climate communication resources with the greatest impact for the climate. Let’s face it: the battle to interpret the climate crisis has been won. We can now redirect the focus of climate communication.

For decades, there have been evidence-based, helpful recommendations on how to convince people that the climate crisis is caused by us (wonderfully summarized on the Skeptical Science website, communication advice for IPCC researchers, university checklists, TED Talks, etc.). Apparently, they have had an impact: even in the U.S., the percentage of citizens who are “alarmed” or “concerned” about the climate crisis has increased from 38% to 53% since 2012 (Yale Program on Climate Communication). In Germany, too, not least the PACE study has shown that we have won this battle: Almost 60% of German citizens are even concerned that we will not meet the climate targets (stable since April 2022, strong/very strong concerns: 36%).

Let’s face it: There will always be a small group of climate deniers whom we can hardly convince (see also interview on klimafakten.de). However, it is not worthwhile to invest in communicating with this fringe group, because the effort required to convince them is just not worth it.

If we want to put our scarce climate communications resources where their leverage for climate is greatest, three areas are promising:

  1. Policy makers (for the legal framework of system change).
  2. Economic decision makers (for supply-side system change).
  3. Personal actions by citizens (for demand-side system change).

In what comes next, I focus on the second area, not because it necessarily has the most impact, but because of my expertise in behavioral economics.

2. Focus on measures, not on climate knowledge!

In a nutshell: The fact is that we don’t really know what we personally can do to combat the climate crisis effectively. And we are systematically lying to ourselves in the process. Changing that is difficult, and more knowledge does not seem to help. Therefore, our climate communication needs to focus on what we can do about the climate crisis.

In 2019, I asked 5000 people in four countries to choose the one with the biggest CO2 impact from a list of seven personal actions. The result was shocking and found its way into many media: giving up plastic bags was at the top of the list in all countries:

This result has been reproduced several times since then (e.g. by Stiftung Warentest) and I also repeated the survey in the U.S. in early 2022 with almost identical results. This means that not only do we have no idea, but also that this is not improving (even in the PACE survey there is only a small increase in climate knowledge since August 2022).

One aspect of this problem is that we not only lack understanding but also choose to ignore it intentionally (perhaps to be able to even look in the mirror in the morning?). Here are two empirical findings:

In 2021, I had 3000 people in Germany and the USA estimate their average meat consumption. When comparing with the real consumption data, it turned out that we Germans eat 77% more meat than we are willing to admit:

According to the PACE study, although almost half of the respondents consider their own climate protection to be effective (Top 2 Box: 22.5%), this does not really correlate with the actual climate-friendly behavior of the respondents (0.33)!

The good news – that’s not a problem, because knowledge does not help: The PACE study uses sophisticated analyses to demonstrate that better climate knowledge is only a very weak driver of personal willingness to act! This is probably the most explosive result of the whole study, but it fits seamlessly into my findings.

3. Focus only on effective measures!

In a nutshell: We ignore even simple help in selecting personal measures against the climate crisis. Which of the selected measures we then actually implement depends neither on their effect nor on their simplicity. Unfortunately, we can only be motivated to take two or fewer measures on average, so all too often, we select measures with little effect.

Our climate communication should therefore only address the most effective measures against the climate crisis and should deliberately omit the less effective ones.

Numerous checklists of personal measures hardly mention anything about the size of the respective CO2 savings. I have always wondered how one is supposed to select the right measures without this information. But the solution is obvious – I thought: You add information on CO2 savings to the checklist and sort it according to the strength of the effect.

To measure the extent of improvement, I presented such an optimized checklist to 1000 people and asked them to select the measures they wanted to follow themselves. 1000 other people (again, representative of German online users) were shown the original checklist (without CO2 savings, measures in randomized order). The comparison of the results was shocking (see the following figure as an example): Sorting and information did not lead to any improvement in the choice of measures! And it was particularly shocking that most of the respondents still selected plastic bags, although it was clearly visible that the CO2 effect is negligible!

One obvious assumption is that we choose the measures that we find particularly easy to implement. But the results of my survey already cast doubt on this, namely when heating replacement (costly, time-consuming) is chosen more frequently than switching to green electricity (cheap, quick). In fact, according to the PACE study, many measures do not differ in their perceived simplicity by the respondents, only “climate-friendly home appliances” are rated slightly more difficult (3.7 out of 7) than the other measures (~4.5 out of 7):

Or consider the following evidence: The “Climate Bet” campaign tried to get people to take effective climate-friendly actions. At the end of this campaign, a survey asked which of the originally selected measures were actually implemented by the respondents in their everyday lives. It turned out that the degree of implementation correlated neither with the popularity or simplicity (=initial selection) nor with the effectiveness of the individual measures: 

That wouldn’t be a problem if each of us took a variety of actions to combat the climate crisis. However, in about a dozen surveys in several countries with a total of more than 10,000 respondents, I have not once managed to get respondents to take more than two actions on average! The average is 1.5 measures, regardless of whether one asks about one’s own plans or about the less socially desirable question of what measures friends and acquaintances are likely to take. In addition, the “spillover” effect from climate-friendly measures to further measures is very difficult to achieve in reality, as the EU-wide CASPI project has shown.

Thus, if our advice simply omits the less effective measures, the climate impact of climate communication can be dramatically increased, as the following two surveys show by comparison:

I conducted a similar test based on the BMWK campaign in August 2022 with 2000 respondents, using the BMWK measures and wording: Focusing on the more effective measures did persuade significantly more respondents to pursue an effective measure (in this case, heating one degree less):

The one-minute commercial by Leaders for Climate Action therefore does everything right from this perspective! The next question is whether this is enough for success.

4. Focus on viral climate communication!

In a nutshell: Even well-done climate communication is too expensive using classic marketing means if it is to have a measurable climate impact at the national level. Viral campaigns in social networks are a possible alternative to roll out effective climate communication at a reasonable cost.

The “Climate Bet” campaign (see above) ended in great disappointment despite its excellent ideas: Of the targeted 1 million (saved or offset) tons of CO2, only around 20 thousand were achieved. Was this due to a lack of marketing know-how? Let’s take a look at a different campaign: In 2021, Leaders for Climate Action (LFCA) succeeded in generating 24 million contacts with its climate communication within a very short time through a large partner network of digital companies. The majority of these contacts were generated via campaign banners on partner sites and they generated almost 200 thousand visits to the campaign website. However, this only resulted in 15 thousand self-commitments to climate actions. So, despite impressive media presence, this outstanding campaign only persuaded a tiny fraction of German citizens to take climate-friendly action:

The marketing figures for this campaign are quite respectable (0.8% click-through rate and 7% conversions on the landing page). This is also evident when comparing it to key figures of the 2022 campaign: There, LFCA was able to reach 85 million people, but the number of people who registered for concrete climate protection measures on the landing page was still in the range of a few thousand, not least because the marketing metrics had deteriorated (0.2% click-through rate, 3% conversions).

A simple “back-of-the-envelope” calculation shows the resulting challenge of classic marketing communication:

Let’s assume we want to persuade enough citizens to take personal action that the effect would be measurable nationwide. To do this, we need – conservatively estimated – at least 10 million people who implement at least one effective measure, e.g., heating one degree Celsius less. If we apply the marketing metrics of the LFCA campaigns (see above), we would need to generate between 125 to 333 million clicks online for this. With common costs of 0.5 to 1.5 € per click (“CPC”), the pure communication costs for this one measure would therefore be between 62 and 500 million euros! By comparison, the BMWK campaign cost around €33 million by the end of November 2022, and Germany’s largest advertiser, Procter & Gamble, spends just over €1 billion a year on advertising. This means that measurably effective climate communication using classic marketing tools is simply too expensive for most players.

Would a PR strategy (i.e., distributing the measures via editorial contributions in the media) be an alternative? The PACE study has shown that trust in the messengers of climate communication is a key driver of willingness to act. Unfortunately, the PACE study also showed that trust in public service broadcasters is similarly poor to trust in the federal government (3.4 out of 7 on a scale of 1 – very little trust – to 7 – very high trust). In contrast, trust in “people and groups who share content on social networks” is significantly higher (4.3 out of 7; trend: increasing).

Therefore, the only way to have measurably effective climate communication at a reasonable cost seems to be via viral campaigns in social networks. (I described a possible approach to this in my TEDx Talk.) In viral communication campaigns, readers themselves take charge of spreading the messages, typically at no additional cost, via social networks and/or electronic messaging, so that no further media budget is required. Unfortunately, this is easier said than done, not least because research in this area is still in its infancy. Meaningfulness of the content and emotional arousal motivate at least some of the readers to forward (cf. Borges-Tiago et al. 2019, Botha, Reyneke 2013)

5. Focus initially on actions targeting heavy polluters!

Heavy polluters such as frequent flyers contribute disproportionately to the climate crisis, but it has been proven that they can hardly be reached by exhortations. Systemic measures such as progressive increases in the cost of frequent flying are an effective lever in this area and are likely to increase acceptance of measures that affect the general public.

The higher our income, the higher our expenditure, the more we consume and the larger our CO2 footprint (depending on the country and time period, a 10% increase in income increases the CO2 footprint by 6 to 8%, see meta-study by Pottier 2022). This leads to a gap in the CO2 footprint between high and low income households by a factor of 10 or more (see Weber, Matthews 2008). An important driver of this is personal flight behavior. As an example, I have calculated this using Lufthansa’s frequent flyer program: The flights that get you “Lufthansa Senator” status quadruple (!) your personal carbon footprint, compared to the national average:

It is estimated that the number of German frequent flyers is between 50 and 150 thousand people, significantly less than 1% of the population. A new study by Cass et al. 2023 diagnoses, based on in-depth interviews and focus groups with this target group, that “high-energy consumers may never voluntarily respond to information, exhortations, and appeals to self-interest. Instead, stronger state actions including those that impinge on ‘consumer freedoms of choice’ are required.” (My own experience with friends and family  fully confirms this.)

Thus, if personal measures fail for high-energy consumers, systemic measures are needed, e.g., progressively increasing the cost of frequent flights through taxes or even limiting flights per person. Acceptance according to a 2018 survey by Kantenbacher et al. is higher for taxation (3.1 vs. 2.7 on a scale of 1-strongly disagree to 7-strongly agree). The PACE study also showed that “taxing millionaires” (with the purpose of helping poorer countries meet climate change standards) receives significantly higher support than bans on certain modes of transportation (strong/very strong support: 61% for taxing millionaires vs. 34% for banning internal combustion engines from 2030).

In general, “pull” measures (e.g., financial incentives) have a higher acceptance than “push” measures (e.g., bans), cf. Drews, van den Bergh 2015. It will come as no surprise that support for any systemic measures drops significantly once respondents are traveling by air themselves (Kantenbacher et al. 2018, Hammar, Jagers 2007).

My hypothesis is that systemic measures for frequent flyers increase the overall acceptance of general measures that affect everyone because it increases perceived fairness (even though this aspect has not yet been studied in a dedicated way to my knowledge, there is empirical evidence for it, see Cai et al. 2010, Brannlund, Persson 2012, Gampfer 2014, Carattini et al. 2018). Therefore, systemic actions against heavy polluters can be key tools of climate communication to prepare the ground for broader action.

Categories
Climate Crisis

Personal actions against climate change: What drives follow-through?

Which of your New Year’s resolutions have you shelved already? The most difficult actions? The ones with the smallest impact? Or is this completely random?
When it comes to actions against climate change, we no longer need to guess:
In Germany, thousands of participants in a grassroots initiative committed to various personal actions against climate change. 🙋🏽‍♀️ Later, they were asked if they had followed through on their commitments. I have plotted the results in two graphs below. The results are quite puzzling:
⚠️ The most popular actions against climate change are NOT more likely to be implemented, even though they are mostly the easier ones to follow through on (left-hand graph)
⚠️ The most effective actions are NOT more likely to be followed through on. (right-hand graph)

Why does this matter? If you give advice to people on what they should do to fight climate change, do NOT list actions with only a small impact! They are not more likely to be implemented and they may crowd out more effective actions.

You would think there are only focused, curated lists of actions against climate change out there, but unfortunately, the opposite is true. So please get out your erasers and curate those lists of advice!

Categories
Climate Crisis

Can we nudge us out of the climate crisis? — watch the TEDx talk:

TEDxWHU

Check out the science behind this TEDx talk:

Section of the talk:Source / media coverage / peer-reviewed research:
1.Have one fewer childWynes, Seth, and Kimberly A. Nicholas. “The climate mitigation gap: education and government recommendations miss the most effective individual actions.” Environmental Research Letters 12.7 (2017): 074024.
2.We have no clue which personal actions matter most against CO2Selected media coverage
Article in F.A.Z.
Interview in Der Spiegel
Infograph in Handelsblatt

A 2022 study in 14 countries confirms that people have no clue which personal actions matter most against CO2:
Stiftung Warentest
3.Americans completely miss the CO2 impact of flying less, and the French misjudge the impact of eating less meatArticle on LinkedIn
4.Over the course of ten years, an average German eats 117 chicken, 4.5 pigs, and half a cow
https://www.blitzrechner.de/fleisch/
5.We massively under-estimate our meat consumption:Article in Der Spiegel
Article on LinkedIn
6.For people like us, the four biggest personal levers to fight climate change are: Fly less, energy-efficient heating, green electricity, and eat less meatCO2 calculator of the German Environment Agency
7.Experts have no clue on which nudges perform bestMilkman, Katherine L., et al. “Megastudies improve the impact of applied behavioural science.” Nature 600.7889 (2021): 478-483.
8.More information does not seem to helpKlein, Nadav, and Ed O’Brien. “People use less information than they think to make up their minds.” Proceedings of the National Academy of Sciences 115.52 (2018): 13222-13227.
9.The effect of a single behavioral intervention is small
(avg. probability of benefit between 6.6% and 14.4%, based on 83 behavioral interventions in randomized controlled trials)		Nisa, Claudia F., et al. “Meta-analysis of randomised controlled trials testing behavioural interventions to promote household action on climate change.” Nature communications 10.1 (2019): 1-13.
van der Linden, Sander, and Matthew H. Goldberg. “Alternative meta-analysis of behavioral interventions to promote action on climate change yields different conclusions.” Nature Communications 11.1 (2020): 1-2.
10.Nudges that directly steer our behavior are 3x more effective than cognitive nudgesCadario, Romain, and Pierre Chandon. “Which healthy eating nudges work best? A meta-analysis of field experiments.” Marketing Science 39.3 (2020): 465-486.
11.People that are concerned about climate change are roughly 50% of the populationYale Program on Climate Change Communication
12.The peer influence of seeing other PV installation is measurableBollinger, Bryan, et al. “Visibility and peer influence in durable good adoption.” Marketing Science (2022).
Categories
Climate Crisis

End filter bubbles or nobody can win

Filter bubbles supercharged by social network sites and digital news platforms are widely seen as a problem. But somehow, everyone believes just “the others” are blinded by them. In this article, I will illustrate that filter bubbles may very well be humankind’s #1 challenge. The time has come to end this unintended but destructive consequence of artificial intelligence. I will show why simple regulation will not fix filter bubbles and suggest a concrete solution.

Take a moment and think back on the last ten years of your life: What has been your biggest personal learning? For me, it has been the value of compromise. I have seen too many of my tried-and-true convictions refuted or at least moderated in real life. Take for example minimum wage: Neo-classical theory told us it would only cut low-wage employment. Turns out reality is a lot more complex on the effects of minimum wage. Turns out reality is a lot more complex on a lot of things! Sorry for being a slow learner, but I finally started to understand why resilient societies are built on facilitating and sometimes enforcing compromise. 

So how do we improve our ability to gain consensus? Recently, I came across a video of an experiment that really rocked my world: People in the street were asked about their opinions on a number of contested issues (like “violence used by Israel against Hamas is – or is not – morally defensible”). When showing the respondent her answers at the end of the short interview, the interviewer used a simple trick to present her the opposite answers, asking the respondent to elaborate. What do you think happened? 

My guess would have been that the interviewers were beaten up in the street, but no! “A full 53% of the participants argued unequivocally for the opposite of their original attitude” (Hall, Johansson, and Strandberg, 2012). 

Obviously, facts did not trigger this sudden change of heart, because facts are still subject to our very subjective interpretation: In their famous study “They Saw a Game: A Case Study, the psychologists Albert Hastorf and Hadley Cantril found that when the exact same motion picture of a college game was shown to a sample of undergraduates at each opposing school, each side perceived a different game, and their versions of the game were just as “real” as other versions were to other people.

What these experiments show is that our attitudes towards alternative viewpoints matter if we want to compromise. Good news: Those attitudes can be shaped (also shown by Leeper, Thomas, 2014). Public broadcasting (for all its deficiencies) has tried this for decades, at least to some degree, e.g., in the UK, Germany, and Japan. 

Yet compromise is joining the list of endangered species these days. Polarization has been on the rise for decades, but it seems to have become a challenge of global proportions. 

What is wrong with polarization you may wonder? There is evidence that a polarized environment “decreases the impact of substantive information“. In other words, facts no longer matter, party lines do. (Interestingly, scientific literacy does not inoculate against extreme viewpoints, while scientific curiosity – aka an open mind – seems to help). 

Still not concerned? Some say that the laissez-faire COVID-19 response in some countries, the Brexit referendum, and of course U.S. presidential elections since 2016 have been shaped by the polarization that is fueled by “filter bubbles” on social network sites. (I am not going to withhold the potential counterargument that polarization has particularly increased in age groups that are less likely to use the internet.) 

Runaway polarization risks political deadlock resulting in more global warming, more poverty, more violent fights for the proper distribution of wealth, water, and healthcare. It can also lead to more autocratic societies. It can lead to more hunger, violence, hatred, distrust, depression, and death. That’s why it is worth taking a closer look: 

“Filter bubbles”(aka “echo chambers”) describe the increasing probability of 

  1. you being only exposed to news that fit your current worldview and 
  2. your personal news feeds becoming more and more extreme.

A fascinating, data-driven analysis by Mark Ledwich shows the traffic flows between various YouTube political channels suggested by the site itself. Apparently, social network sites have inadvertently fueled the growth of filter bubbles not only by providing an efficient means of content distribution for basically everyone (it is not without irony that you most likely read this article on a social network site) but primarily by using machine learning algorithms that dramatically exacerbate the problem. This is at the heart of this, so we need to dig deeper. 

If you have not yet seen Netflix’s “The Social Dilemma” documentary, let’s take a brief look under the hood of your news feed. It’s worth spending a minute on the fundamentals of this phenomenon. Please bear with me and make an effort to understand this – it is important, really important. (Why? Because politicians around the world so far seemingly did not take the time to get it and consequently failed to act effectively!)

Naturally, digital media sites want us to keep reading, they want us to stay engaged. This is a perfectly legitimate objective for any commercial website because user engagement = time on the site = ultimately ad revenue. Since each of us responds differently to different pieces of content, they tailor each and every news feed. To do this for millions of different users, social network sites use deep learning artificial intelligence algorithms. These algorithms are constantly trained to predict the potential user engagement of every piece of content in your news feed. Training works like this: They take the content, language, and visual information of a post as input information, and then they measure actual user engagement (comments, shares, likes, etc.) as the desired outcome. Based on this closed feedback loop, the algorithms continuously predict what drives user engagement based on real-life data. This works just like Google being able to predict whether or not a picture shows a cat or a traffic light using examples that have been categorized by a human (“supervised learning”). 

And this is the key reason why it is wishful thinking to assume that social network sites will fix this themselves: these algorithms are one of the cornerstones, perhaps THE key ingredient to their ongoing success! 

One of the key triggers of user engagement is fake news because they travel “farther, faster, deeper, and more broadly than the truth” (as shown in the landmark study by Vosoughi, Roy, and Aral, 2018). That’s why they are prioritized by algorithms. But fake news is just one element of the problem. More importantly, extreme political views that reinforce users’ own opinions presumably follow the same path. That’s how they contribute to dangerous filter bubbles. Make no mistake: Social network sites are actively fighting fake news on various fronts, like restricting the activity of bots and adding friction to sharing certain news. But they would never abandon the core reinforcement logic that drives their news feed algorithms. 

It seems like a classic “prisoners’ dilemma”: Each social network site has an overwhelming incentive to use these algorithms because everybody else does it, too.  

The only way out? You guessed it. Someone has to force all of them to change. In comes government regulation.

However, in the past few years, much of the public debate and regulatory action has focused on the “fake news” aspect. For example, this year, France decided to establish a new anti-fake news agency to fight fake news coming from foreign sources (if you wonder what the 60 people initially assigned to this job can achieve, I am asking myself the same question, especially when you look at Facebook’s 10,000+ staff to fight illegal content…). Ahead of federal elections in Germany, Facebook is running an ad campaign on how they are fighting fake news:

No alt text provided for this image

Why the focus on fake news? Here is my little piece of conspiracy theory: Social network sites focus the discussion on fake news because that decoy is something that they can actually address. Few people seem to get that this is just a symptom of the underlying machine learning algorithms. Fixing fake news will not fix filter bubbles.

This April, the European Commission issued draft legislation on artificial intelligence and suggested “a regulatory framework for high-risk AI systems only”. However, the artificial intelligence that governs our news feeds on social network sites did not make it on the list of “prohibited” or “high-risk AI systems” (as outlined in Annex III), at least not yet. That needs to be fixed a.s.a.p. Also, the regulatory actions suggested (“requirements for high-risk Ai systems”)  are very generic and focus on risk management procedures, leaving plenty of room for interpretation. If social network sites’ algorithms were to be added to the high-risk list, I would not be surprised to see this hashed out in courts for decades to come before anything happens. 

We don’t have that much time anymore. We need to be much more specific when we, the citizens, address this key threat to consensus and we need to do this now. 

A Counter-Algorithm for Content Display

Imagine a world…

  • where digital media still give you the exciting content that you (don’t know you) want to see – but at the same time, they expose you to insights that challenge your existing beliefs in a constructive, effective manner,
  • where social media fosters the effective exchange of ideas and debate by incentivizing respectful language,
  • where citizens still have diverging interests, perceptions, and opinions, but are enabled to explore solutions that serve most of us.

We want to explore a solution that uses the power of machine learning instead of trying to fight or destroy it. 

Science has already developed procedures for decades that effectively achieve consensus and change minds (Janis and King, 1954, recent and very relevant: Navajas, Joaquin, et al. 2019, corresponding TED Talk). Why should it not be possible to automate this and integrate it into the digital world? One challenge is that these concepts mostly rely on interpersonal contact. However, experts hypothesize that limited tweaks to algorithms may be sufficient to “limit the filter bubble effect without significantly affecting user engagement”.

Let’s summarize the scientific evidence on what we need to gain consensus: No alt text provided for this image

Our starting idea is simple: To gain consensus, we need to learn to embrace the counter-arguments. But – and this is a fairly new and big “but” – research suggests that simply being exposed to counter-arguments in your news feed actually increases polarization instead of decreasing it (I routinely force myself to read articles in the Fox News app and I am living proof of that effect). This happens probably because content is mainly addressed to in-group peers. Consequently, this content tends to be extreme and insulting to dissenting opinions, because this drives engagement and group-think. However, this naturally also decreases the likelihood to convince others. As we learned from Navajas, Joaquin, et al. 2019, moderate opinions are much more likely to win over other people’s opinions. 

Instead of simplistic rules and generic regulations like the one suggested by the European Commission, we suggest harnessing the predictive, self-optimizing intelligence of machine learning. This is what we think will work:

  1. The existing algorithms that govern the news feed stay untouched. This is necessary for any platform to remain engaging. Without these algorithms, any platform eventually becomes worthless because most content will be irrelevant for us. They fill our echo chamber with “filter bubble content”. 
  2. Now we need to add “counter-content” that is effectively challenging our current beliefs (which are already reinforced by “filter bubble content”). How does this work? As described above, deep learning algorithms are trained to predict the engagement of any piece of content. The same algorithms can also predict whether or not a piece of “counter-content” is decreasing the likelihood of engaging with “filter bubble content”. 
  3. The power of artificial intelligence will find persuasive tactics we may not even be aware of today. Think of it as two algorithms constantly hashing it out. Those algorithms can become much more effective than any televised U.S. presidential debate. Why? Because this algorithm will be trained not just to mobilize its own followers but also to convince other followers. 

Interested in the details? Here is how AI veteran and expert Frank Buckler describes it: 

  • P denotes a person so that the algorithm can adapt to her interests.
  • Let C be a set of information that describes a piece of content by using its text and visual information (“filter bubble content”).
  • L(C, P) is the likelihood that person P will engage with content C and has to be maximized. The mathematical function that calculates L based on C and P today is shaped by social media’s deep learning algorithms. It is not necessary to understand how they work. It is important to accept that they can estimate any unknown functions that predict L based on C and P if P has interacted often enough with different kinds of content C in the past. The more the person interacts, the better the prediction becomes.

What we now suggest is to include more information:

  • Let CC be a set of information that describes a second piece of content that is exposed to the person simultaneously or in close succession (“counter-content”).
  • L(C | CC, P) is now the likelihood that P engages with C given CC is exposed and has to be minimized.
  • The content C itself is minimizing the engagement with CC [=min L(CC | C, P)]. This makes sure that counter-content CC is contradicting and does not further exaggerate content C.

Is there a better solution?

Let’s summarize other potential solutions under discussion:

  • Outlaw filter algorithms: As described above, this would impair the usefulness of content platforms so severely that this functionality is likely to happen illegally and/or indirectly. The same would happen if we outlawed filter algorithms just for politics or tried to ban political posts altogether. 
  • Introduce a mandatory “Driver’s License” (to use social network sites): While this may improve respectful language and help people to recognize fake news somewhat, it does not address the underlying problem: systematically misleading information and flawed learning through the selective presentation of information.
  • Increase support of public broadcasting: Unless public broadcasters use similar algorithms they will never stand a chance against digital media platforms that supercharge their user engagement with deep learning algorithms.
  • Mandate generic risk management for deep learning algorithms (like the proposed EU directive): Since these algorithms are mission-critical for the platforms’ success, generic legislation that leaves plenty of room for interpretation will inevitably result in decades-long court battles. Introducing a mandatory code of conduct for platforms’ use of deep-learning algorithms is likely to have the exact same effect. 

This Article is Useless

…unless you comment and share it. 

My intention in writing this article is to explore how we can change the world for the better. I want to directly influence policy-making on digital media. However, no article alone can achieve this. Only if readers comment and share this article, only if it becomes viral, will it have the chance ever to matter.

This is why I am asking you to comment and share your view. 

This is why I am asking you to share this article as broadly as possible.

If you think this article is bogus, PLEASE COMMENT.

If you think more people should read this article, PLEASE SHARE.

If you agree with my conclusion that we need a smart solution like a counter-algorithm to save our world,  PLEASE SHARE.

In any case, make up your own mind, but always remain curious.

Categories
Climate Crisis

Fighting Our Food Fallacy

Eating less meat is one of the top drivers to bring down our personal CO2 footprint (and no, using fewer plastic bags does not make the top ten list). That is one of the reasons why plant-based food is hyped these days. But after surveying more than 5,000 people in the US and Germany, the truth is that we massively underestimate how much meat we still consume. That begs the question of how to encourage more sustainable food habits. 

If you live in the “climate crisis” filter bubble like myself, you get the impression that everyone is happily munching on plant-based food 24/7 these days (recent sales data points to exponential growth). In 2020, 400,000 more Germans claimed to be vegetarian than the year before. Yet, per capita consumption of meat across OECD countries has actually increased by close to 9% since 2010.

Now try this: When speaking with friends, casually drop the message that you have become a vegetarian. My guess is that in 8 out of 10 cases, your friends will feel compelled to respond like this: “Oh well, actually, you know, we really don’t eat meat that much anymore, do we, honey?”

It seems that being a vegetarian (or consuming less meat) is becoming the “socially desirable” answer. This is great if it heralds a new social norm of more sustainable eating behavior. However, it also means that we are more likely to lie (to others and ourselves) about our true meat consumption.

To get to the bottom of this, the Donanto Foundation sponsored a series of simple surveys in the US and Germany. Here is what we started with: “Please estimate: How much meat do you personally eat on average per day? (Please remember to include meat in frozen meals, convenience food, when eating out, cold cuts, etc.)”

We gave respondents seven answers to choose from and since people have trouble estimating meat weights, we explained each option briefly:

(Nerd note: We randomized this list of options for each respondent to eliminate potential order effects. The analysis was straightforward: If we have a sample of respondents that is representative of the overall population (aged 18+) and multiply the percentage frequency of each choice with its individual meat weight, we can add up the average per-capita meat consumption and compare it to the real average meat consumption.)

Personally, I was not surprised that respondents’ personal average was lower than the real average meat consumption. What did surprise me was just how much we are off: We actually eat 71% more meat than we think in Germany and 49% in the US.

To put this in perspective: Over the course of a year, each of us eats an additional five chicken, plus one-fifth of a pig, plus 2% of a whole cow more than we think (rough estimate based on the German meat mix). I am no psychologist, but perhaps this is an extension of the Dunning Kruger effect, where “people are typically overly optimistic when evaluating the quality of their performance on social and intellectual tasks”.

(Nerd note: You may think this is because respondents had trouble allocating their meat consumption to an average day. To check, we asked another 600 people the same question, only this time we asked for their meat consumption over an entire week. Lo and behold, the weekly respondents were even further away from reality than the daily ones!)

To test if we can eliminate the social desirability bias and tap the wisdom of the crowds, we repeated the survey with a slightly different question (in Germany): We asked respondents to estimate the daily meat consumption of the average person, not for themselves.

Well, what can I say, the wisdom of our crowd was much better than their personal estimate, but still not great overall: In reality, we still eat roughly 24% more than respondents estimated.

You probably noticed that I have been withholding the real meat consumption figures. So here comes this ugliest of truths: On average, each of us eats about 280 grams or roughly 10 oz of meat EVERY F***ING DAY! That’s in the US, in Germany, it amounts to 160 grams.

Wow. I’m going to let this sink in for a second.

Even after adjusting for some spoilage, plate waste, and other losses in grocery stores, restaurants, and homes, these numbers are still stunning, since they include everyone who cannot or will not eat meat.

OK, so excessive meat consumption is a major driver of climate change (and bad health), yet most of us fail to recognize how our own consumption is fueling this. Now let’s step back and think about what to do with this insight.

Here is a crazy thought: What about applying some learnings from smoking cessation programs? Smoking cessation has been under scientific scrutiny for decades, so there is a host of valuable knowledge out there, for example:

  1. Smoking cessation follows specific stages (precontemplation, contemplation, preparation, action, and maintenance), and “how much progress patients make after an intervention is directly related to what stage they are in prior to intervention”. If most meat-eaters are in denial about how much they really eat, perhaps we need to target earlier phases of their process.
  2. Over a hundred studies show that making tobacco more expensive is “a powerful tool for reducing tobacco use” and that tobacco taxes are not very regressive due to the high price sensitivity of low-income smokers. Therefore, the current discussion on increasing meat prices in Germany, e.g., by means of a surcharge to finance more animal-friendly farming (“Tierwohlabgabe”), may have a positive side effect.

If you are already in the “action” stage and would like to do something about your personal meat consumption, bear in mind to start small, but with consistency, for example, try to skip meat for lunch every Friday. If that works, move on to grander plans, like ProVeg’s free online 30-day Veggie Challenge. Good luck!

Categories
Climate Crisis

The stunning impact of frequent flying

My dear fellow frequent travelers – COVID-19 has grounded most of us (…and deprived us of bland lounge food).
In case you are wondering what the one thing is you can do to slow the climate crisis: LET’S….JUST…DON’T…FLY…AS MUCH when lockdowns lift!
The numbers tell a stunning story (check out the graph below): The flights that I would need to retain gold status at Lufthansa cause three times the CO2 footprint of an average German citizen!

Categories
Climate Crisis

How Our CO2 Journey Began

After I had offset the CO2 emissions of our family summer vacation, I also wanted to better understand what more we could do personally to cut our emissions. I found all sorts of resources on the web, but they seemed either much too broad or much too narrow in focus.

post

Instead, I was looking for a concise, quantitative, prioritized list of key CO2 emission sources that I could concentrate on. I was so intrigued by this idea I even drafted a dummy version (see screenshot below):

My initial dummy list of personal levers to reduce my personal CO2 footprint

A number of specialized NGOs I contacted with this dummy version really liked the concept, but did not have anything ready to share. So I ended up researching the facts myself during one internal meeting that was particularly boring.

Turns out there is an incredible amount of well-researched data on CO2 emissions available out there at your fingertips! However, you really have to be a data-savvy expert to make sense of it! So I invested a few hours to research the most important facts and compiled them in a simple spreadsheet. Then I had an enthusiastic colleague (Carsten) help me out triple checking the facts and expanding the list.

That initial analysis contained quite a few surprises for me personally: For example, I had substantially under-estimated the CO2 impact of switching to a vegetarian diet! And I was very surprised to learn that avoiding plastic bags had basically zero impact on my CO2 emissions.

I started wondering if my fellow citizens had the same misconceptions on what were the key levers to cut personal CO2 emissions. Since easy-to-use insights were inaccessible and most lists lacked numbers, it seemed only natural that everyone would be just as clueless as myself.

Five surveys (with a total of more than 6,000 respondents in four countries) later, we were able to confirm that hypothesis! Our most striking finding: People across the world believe that avoiding plastic bags is actually by far the most important personal lever to cut CO2 emissions.

When we published those findings in a simple blog post on LinkedIn, things got really wild: the post generated 10x more views than my next best post and its core graph gathered thousands of likes on Reddit within a few hours. Within a few days, the story got picked up by multiple national media outlets as well as a few international ones like Wired UK or Treehugger.

Selected press coverage of our study results by Germany’s largest and most prestigious newspapers and magazines

The most beautiful and fun implementation of our findings was done by Handelsblatt, Germany’s leading business daily: Not only did they publish our insights in their “graph of the day” category covering two full pages, but they also created an animated version here.