In the Mind of a Climate Skeptic

[UPDATE July 25, 2019: Whether you believe in man made climate change or not, the solution is the same: Gen IV nuclear. Follow Bill Gates’ lead on this. So let’s just look forward together!]. On to the orig post…

I’ve become a climate skeptic. Before you bash me, at least read why. I am absolutely open to continued, productive, positive dialogue. My opinion is absolutely subject to change, if presented with pertinent information that I’ve not seen before.

This is going to be a very unpopular post amongst many of my friends and family. But please bear with me. I am absolutely open to continued, productive, positive dialogue. My opinion is absolutely subject to change, if presented with pertinent information that I’ve not seen before.

I used to be a Global Warmist. In 2006, Al Gore’s documentary, “An Inconvenient Truth” presented a very convincing case for man’s effect on the climate and the disasters that lay ahead if we don’t change.

Around this same time, I moved to Los Angeles. The smog seen when you look at the hills or at the city from afar is disgusting. I then discovered research papers hypothesizing the correlation of air pollution to asthma.

So, while my opinions on man-made climate change have shifted, I am absolutely on-board with Clean Air initiatives, so I remain directionally-aligned with Global Warmists.

Where I and the Global Warmists diverge is on the solution and this is really the key to everything. I (currently) do NOT believe that we are on a devastating trajectory course for Earth, as indicated by the latest reports highlighted in the mainstream media (MSM). I don’t think we should be applying huge carbon taxes on businesses (which will ultimately hit us, the consumers) and providing Governments with more money to waste.

At the very least, based on the science that I’ve come across, I’d like to see us wait a couple more years before doing anything drastic. I will lay out my thinking in this post.

For a cliff notes version, this is a great summary of a perspective that I agree with: This video clip is of Professor Jordan Peterson’s response to a question about the potential for climate change to be a humanity-uniting issue. Short answer (para-phrased): “No. It’s a complicated issue and there are higher priority problems to solve.”

Look, we’ve all heard the line: “97% of Scientists agree…”. That line has been over-used and over-loaded. Some media and personalities often omit the word “Climate”; I believe it’s supposed to be: “97% of Climate Scientists agree…”. And agree on what exactly? That man-made has an effect at all? Or that man has created and is the cause global warming?

My skepticism changed very slowly over time and I didn’t actually cross the line to full-blown skepticism until this year (2018).

It all started…

Back in 2011, I was at a neighbor’s bbq and I met a Geology professor at a local college or university. Somehow the topic of global warming came up and this professor was very adamant that global warming was a big crock. I was flabbergasted. I was blown away that a highly-educated person and someone in his position would think this. But honestly, I had no ground to stand on. I could not combat any argument intelligently; I only knew what I’ve heard from MSM and Al Gore’s documentary “An Inconvenient Truth”.

Also, I’d been reading ZeroHedge for a while now. It started as a financial blog in 2009, really writing about all the wrong-doings of Wall Street and how they caused the financial crisis. So, the view points are definitely anti-establishment. It’s branched out over time into politics and what not. It’s now more of a content curation or blog aggregator site, but it maintains it’s anti-establishment roots. This is where I found Martin Armstrong.

I started to follow Martin Armstrong for his economic forecasts. He has developed a computer algorithm that is widely sought after and he supposedly advises multiple foreign central banks. Full disclosure, he’s definitely right-leaning and anti-establishment, politically. His algorithms predict economic cycles. His models suggest that we are actually entering an economic downturn in correlation with a Global Cooling period. [Note, if you read his stuff, don’t conflate economic downturn with stock market prices.] In any case, since he opposes the Global Warming view, against the mainstream, he shares research that he comes across to debunk the MSM narrative.

I’m still a Global Warmist at this point.

Then in 2015, Scott Adams enters my life. I’ve been a Dilbert comic reader for a long time. In August 2015, Scott Adams wrote two prescient blog posts: and

On November 8, 2016 Scott Adam’s credibility shot through the roof!

Scott Adams clearly sees things that others cannot. This guy is worth paying more attention to. Here are his collection of blog posts about climate change: What Scott Adams introduced me to was doubt; doubt in the validity of the models that climate scientists use.

Okay, so Scott Adams has cracked open my curiosity and has me questioning my views about Global Warming and man’s cause/effect. So I start to researching opposing views. What science are the climate skeptics looking at?

I’m no scientist and I can’t pretend to understand half of what all these folks (on both sides) say. BUT, the pattern that I noticed is that the scientists who OPPOSE Global Warming were not Climate Scientists, but they were Geologists, Physicists, Mathematicians; i.e., Scientists from other fields! Hmm, remember the Geology professor from 2011?

Is it possible, that we (humans) are just a tiny part of a much larger system? Is it possible that Climate Scientists have personal gain by being a Global Warmist (or avoidance of personal shame)? The Earth and its climate have been changing for millions of years. You know, plate tectonics and the ice age, kind of thing…

I believe (and please fact check me here) that the primary models that climate scientists use a wide variety of measurements from Earth (surface temp, ocean temp, volume/thickness of ice, etc). But they incorporate into their models, the greatest energy input parameter, the Sun. Hmmm… [More on this below]

Are Climate Scientists simply tuning their models to fit their desired narrative. See “The Art and Science of Climate Model Tuning“.

In this article: “U.N. Predicts Disaster if Global Warming Not Checked”.

A senior U.N. environmental official says entire nations could be wiped off the face of the Earth by rising sea levels if the global warming trend is not reversed by the year 2000.

Coastal flooding and crop failures would create an exodus of ″eco- refugees,′ ′ threatening political chaos, said Noel Brown, director of the New York office of the U.N. Environment Program, or UNEP.

He said governments have a 10-year window of opportunity to solve the greenhouse effect before it goes beyond human control.

This was published in 1989! That model clearly failed.

As recently as October, IPCC published a report and CNN’s reporting (and all other MSM, to be fair) of it is eerily similar to the article from 1989:

The report issued Monday by the UN Intergovernmental Panel on Climate Change (IPCC), says the planet will reach the crucial threshold of 1.5 degrees Celsius (2.7 degrees Fahrenheit) above pre-industrial levels by as early as 2030, precipitating the risk of extreme drought, wildfires, floods and food shortages for hundreds of millions of people.

A month later, the entire study was debunked. The model had math errors and the authors admit it renders the model useless as the margin of error is too big. This is exactly what Jordan Peterson eludes to in the video above (as you extrapolate the models into the future, the margin bars become too big). Of course, you really didn’t hear about this news in the MSM.

Even more recently, which again garnered the attention of MSM, the US Government (U.S. Global Change Research Program) issued a similar report. In this report, they project out to the end of the century. That’s 80 years! Firstly, this is assuming 0 innovations in technology. The odds of that are 0%. That alone debunks this report. Secondly, it suggests a drop of 10% in GDP. This sounds scary until logic kicks in: US GDP per capita is projected to triple by the end of the century, so 10% reduction from an economy 3x the size of today isn’t so alarming.

Okay, but what about the opposing science?

I really like the Sun Spot theory. This is a great video explaining it: This hypothesizes that the sun plays a greater role in Earth’s climate than anything. And it’s a cyclical occurrence, and hence, predictable. Professor Valentina Zharkova (Prof of Mathematics) is predicting that we’re entering a Global Cooling period with an upcoming grand minimum between 2020-2055.

Let me repeat: An upcoming Global Cooling period.

NASA research corroborates this theory. A NASA researcher predicts a global cooling period is upon us:

“High above Earth’s surface, near the edge of space, our atmosphere is losing heat energy,” says Martin Mlynczak, a scientist at NASA’s Langley Research Center. “If current trends continue, it could soon set a space age record for cold.”

Remember, Martin Armstrong, through a completely different model — an economic model — predicts Global Cooling in roughly the same period. His historical research correlates major economic downturns with cooling periods.

Doesn’t this speak volumes that 3 individuals looking at something from completely different angles reach a very similar conclusion?

The good news about this theory is that we will know whether this is valid or not within the next few years. I will be watching!

So, let’s not act so fast and take drastic measures to tax ourselves for something that isn’t definitive.

Besides, when it comes to clear air, we’re on the right track (the US at least):

What do you think? Am I crazy?!

AI Wins Again!

AI beats humans again!

These victories are to be celebrated as great feats of technology and advancement, until one day… :/

In this competition, lawyers we’re given 5 NDAs to review and identify 30 legal issues.

Humans averaged 85% accuracy rate; AI achieved 95 percent accuracy.

AI also achieved 100% accuracy in one contract, whereas which highest-scoring human lawyer score was 97%.

So, the tech works, but what is the business case?

Human lawyers took an avg of 92 minutes; AI completed the task in 26 seconds!!!

That is at least several hundred dollars of savings.

I’m not a lawyer, but if I was, this isn’t something that I’d be concerned with at all. I’d welcome this with open arms and run to this now, as a potential competitive advantage to provide a better service at a lower cost to my clients. In theory, I’ll be able to serve more clients as well and/or be able to devote more attention to higher valued services.

As a consumer, I’d look for lawyers that have adopted this kind of technology because I will feel more confident in the quality of the service. And presumably, the service might be a little cheaper (relative to others’ that don’t leverage technology).

How Romantic…

Firstly, I didn’t even know that Japan had a royal family.

Secondly, love conquers all.

Thirdly, don’t feel bad for the princess. She still receives a lump sum of money after leaving the royal family to “maintain her high standard of living”.

Kei Moriya: Big score for the little guy. Keeping the dream alive for us commoners! (to be clear, not my dream, I’m happily married!)


Is Sexual Abuse in the Church part of the Institution?

60 minutes lead story this week was about a whistleblower that came forward with evidence of sexual abuse allegations going on in the churches in Buffalo for decades and the leaders knew about the incidences, yet kept looking the other way.

I’m not religious, but clearly these leaders are serving themselves and not serving their people.

This problem seems very pervasive in Buffalo. Is it pervasive throughout other parts of the country as well? I don’t know, but my suspicion is yes. If it were just a region, then it would be easy for the Vatican to purge one region.

The fact that this has gone on for decades and that there are so many cases, makes me believe that this is institutionalized. Were they abused themselves as children in the church? Do these men then seek priesthood in order to put themselves in a position of power over kids to abuse them?

Absolutely disgusting!

Doubly so when it comes from people who are supposed to be the “holiest of holy”

How Much Time do you REALLY Have?

Would you change anything if you, literally, knew when your time is up? Seems we each have an explicit biological clock embedded in our DNA.

This article talks about how researchers found that your Epigenetic clock can calculate biological age and predict your lifespan.

“Some individuals who fill their lives with fitness and healthy habits die younger than peers who live a much less healthy life. New research into the epigenetics of aging sheds some fresh light on the perplexing phenomenon of premature aging.”

It’s based on this research paper.

I thought this was super interesting.

Loads of implications:

  • Would you retire earlier or later based on your biological age?
  • Surely, this is going to have a tremendous effect on the Insurance industry.
    • I wonder how long until the industry adopts this as common practice to set your premiums.
  • Now that we know the marker (or measure), can we work to improve or manipulate it. (this is all over my head, I don’t even know if that’s a valid question)

Smart People are Flip-Floppers

I’m insecure. I have a small fear of commitment. When I make a decision, I’m always wondering if it was the best decision. What’re the unknown unknowns?

Bezos believes that “the smartest people are constantly revising their understanding, reconsidering a problem they thought they’d already solved”

I’m not saying I’m amongst the smartest or smart at all. But this did give me solace, in that, at least I know I might be thinking along the same lines as smart folk.

I’m always curious: Is there a better way?

In the book “Thinking in Bets”, Poker pro Annie Duke says that when it comes to decision-making, decide as if you are betting all of your money on your choice. Don’t take shortcuts based on your biases; seek contrarian opinions and experienced counsel. Talk with folks who have had similar experiences and expertise who can critique your choices and illuminate your blindspots.

I’ll talk to anybody and everybody about anything.

You can always learn something from someone.

And you know what? You’ll probably disagree and hate me for saying this, but Recruiters and Sales folk are amongst the best to speak with because they speak to the most people. So, they often have a good perspective (as long as you understand their bias, you can really learn a lot).

Rise of the Chief Data Officer (CDO)

Image shows number of CXOs in USA for companies with >1000 employees. In other words, only ~5% have a Chief Data Officer (CDO). Yet, how many are undergoing “Digital Transformations” and/or trying to become “Data-Driven” and/or trying to leverage AI (which depends on (good) data)?

I believe that the CDO role is a huge gap at corporations and it presents a huge business opportunity; not to mention a probable necessity going forward in order to, just simply, compete.

If you segment just “Retailers”: CEO = 497 | CMO = 154 | CDO = 8

This means in Retail, only 1.61% of large retailers have a CDO!

My advice: Hire a CDO.

Here’s the ROI: We all know data is siloed. But instead of breaking silos, I see LOBs duplicating data across the org to suit their needs; thereby creating bigger silos. That’s a lot of duplicated expense and effort, as indiv LOBs protect their budget and interests.

Example, one company recently spoke with, Marketing and Analytics use Adobe Analytics. But Data Science chooses to use raw web logs.

A CDO can put the people, processes, and tech in place to streamline data across the org.

N.B. All #’s are from LinkedIn Sales Navigator, so probably not exact, but good enough for % analysis. Also, I included “Chief Analytics Officer” in the CDO category.

Makes “Hew” say Hmm

Life After Death? (if you can afford it)

I suppose when you have millions of dollars at your time of death, there is no harm in spending $100K for a lottery ticket to be brought back to life one day.

This is a genius business model. In some regards, I think Evil Genius, but then again, who’s getting hurt? There is no con. But the current owners of the company, whom profit from this venture today, take $100K, put you in cold storage, and head to the beach? No worries about customer service or a customer complaining about bad service!

Does this fee include the revival surgery process?

Let’s say this technology does come to fruition in 50 years or 100 years. You’ve already given away your estate. You’re no longer ultra-wealthy. Are your (potentially ungrateful) great grandkids, who never knew you, going to take care of you?


Really Japan?

Japanese are so interesting. They insist on preserving their strong culture with very strict immigration policies.They’re already one of the oldest populations in the world. Their birth rates have plummeted. And now the men are preferring sex dolls over the real deal?


Good Premise, but Dangerous Means?

I am all for legalization of Marijuana. It’s long overdue. I don’t know the exact stats, but I’m sure that there are far too many folks currently incarcerated or blackballed with a criminal record because of minor marijuana charges.

But I don’t believe that a DA’s office should be allowed to do this. This is one man, single-handedly, changing the law, isn’t it? Doesn’t that set a dangerous precedence? Why doesn’t this go through the municipal or state government?

Data Wrangling is Career Strangling

Data wrangling is a necessary process when working with big data; most data, in reality. This opinion piece is not to diminish its importance. Nor, is this to be confused with Data Engineering. But I will argue that data wrangling is career strangling, in that it is holding you back in your career progression. Let me explain…

Firstly, let’s agree that the whole basis of big data is to whittle it down to little data, that we call “Insights”. The point of any data analysis is to identify a trend or anomaly. The point of a machine learning model is to find a set of defined patterns or assign a probability.

Observe any Data Scientist or Analyst presentation and the only pieces that get talked about are the Insights and the model. Zero time is spent explaining how the data was wrangled, despite that being 60-80% of the effort.

I am making the argument that data wrangling is low-level, tedious work that is wasted when an expensive resource such as a Data Scientist or Data Engineer or Analyst decides to take this on.

The best consultants know that:

You don’t get paid for the hour. You get paid for the value you bring to the hour

The more time you spend on lower value work, the more you diminish your value.

And if you’re an Analyst / Data Scientist spending a greater portion of your time wrangling data, that’s much less time that you’re spending to understand the data, that’s much less time you’re spending to analyze the data, that’s much less time to you’re spending on delivering business value from the data.

When it comes to big data, I believe that folks are starting to realize that robust software engineering practices need to be put in place to ensure quality of the data pipeline and #datagovernance. …Cue the Data Engineer.

In today’s episode (Aug 14) of the Digital Analytics Power Hour (a wonderful podcast, btw), there was a great discussion about raw data and data virtualization. I didn’t feel that there was any consensus, so I’ll throw in my 2 cents.

A company must adopt a tool or process to virtualize the raw data for the Data Scientists and Analysts. Drawing from software principles, the solution — built in-house or purchased — must be robust, scalable, extendable, and re-usable.

This will save an immense amount of time (and headache).

For example, when working with raw clickstream data, you have billions of atomic events. In most cases, identity resolution is required over a specified period of time. If every Data Scientist or Analyst is starting with the raw data, I guarantee that each will resolve the identity in a different manner (different “code”). This leads to multiple, inconsistent “truths”. The Analysts / Data Scientists should only work from a consistent, consolidated schema for the vast majority of cases.

So, when I say “Data wrangling is career strangling”, it’s because you’re devoting too much time to work with a lower-assigned value.

[Tangential annecdote: I use Salesforce a lot in my work. If I’m to be diligent, the data entry could be up to 4 hrs a week. I hired a VA  on my own dime  to handle this. This allows me to spend more time on higher value (and quite frankly, more fun) tasks. I value my time]

In the end, businesses are results-oriented. If you can produce more positive business results in a shorter time frame, then your career trajectory will move up-and-to-the-right at an accelerated pace.

And it’s a compounding factor. Those that produce results are provided more opportunities. The sooner you produce results, the sooner those opportunities present themselves.

Focus on value delivered.

The faster you iterate, the faster you grow.

Why you should Build your CDP

Customer Data Platform (CDP). The more I read and learn about CDPs, the more I am convinced that most, large companies should have one. The CDP hype is real. BUT (I like big BUTs and I cannot lie), I’m a huge advocate for BUILD (Vs. Buy), in this case. I would not go with a CDP SaaS vendor.

Of course, there is always exception to the rule and, as with anything in technology fitting, it depends. But I would strongly consider to build in-house, by default.

This is a shift from my norm. I’ve always been on the vendor-side of things, in favor of the business case to BUY solutions. But, I see this as so strategic and core to a company, that it’s worth the investment to build it. There are tools on the market today to make this process feasible and achievable (more on that later).

When Caesars Entertainment declared bankruptcy a few years back, “The most valuable of the individual assets being fought over by creditors is the data collected over the last 17 years through the company’s Total Rewards loyalty program”. I’m going to argue that that is their CDP. This is a good write-up about it:

When you build a CDP, you are building an incredibly valuable asset.

Value is built through asset ownership, not renting.

Taken from this article (, the CDP has three primary functions:

  1. They pull in customer data from the disparate data systems of your choice
  2. They match, merge and cleanse this data into a unified record for each customer
  3. They make these records visible to your other marketing tools to ensure the consistent treatment of customers

I’m going to add #4, from this Gartner blog (

4. It is owned and operated by marketers

I like the way the author opened the article:

A new technology appears, seemingly from the ether, and promises to change our lives. Customer data integration, labeling and storage problems will disappear. Identities will merge. You’ll be able to find new audiences until your ribs squeak and deliver them to any execution system in the barn.

Oh, and it will scale, rarely fail and enable (yes) true one-to-one marketing.

The name of this magic machine is … CRM. It was 1998. Companies piled in, dropping $3.5 billion a year on apps and databases alone – consulting fees not included – and yet, by 2001, 50% of CRM projects “failed.”

The same thing happened, on a lesser scale, during the great marketing automation boom of the 2000s. And it’s happening again.

So, the CDP is supposed to accomplish what the CRM cannot do and what the DMP does not do. But we cannot forget Primary Function #4: It is owned and operated by Marketers.

If you thought the relationship between Sales and Marketing was challenging, it pales in comparison between the diatribe between Marketing and IT; hence, the rise of Marketing Technology teams? I wrote a post about this recently and highlighted this article by on chiefmartec by Scott Brinker, written in 2009 (the classics never die) .

Let’s be honest, these are massive projects; however, the potential value is huge. It’s no surprise that there are over 60 vendors in just a few short years, with a few of them pivoting to adopt this acronym as their primary identity. This is a project you only want to do once.

Do you want to be vendor-locked?

Many CMOs may not even live to reap the full benefits of their investment, given that the median tenure-ship of a CMO is 31 months (according to this source )

You have a CRM.

You have a DMP.

You have a Marketing Automation platform.

You have an EDW and possibly a Data Lake.

You have an enterprise BI solution.

Do you really need a CDP vendor?

(And I’ll double down on that question, if you’ve already implemented a SaaS Customer Journey solution, which most CDPs can/should be able to provide)

The one case where I’d fold quickly on the CDP vendor case is Datorama, if and only if, you’re already full stack Salesforce —negotiate hard at renewal time! 🙂

Here’s the kicker, the most expensive (and important) component of the CDP is your 1st-party behavioral data. The storage, but mainly the processing, of your digital analytics clickstream to match, merge, and cleanse this data into a unified record for each customer. That’s a lot of data! And you’re likely already storing it somewhere.

And if you’re a brand conglomerate, do you have a CDP per brand or do you aggregate or can you have both? I think you should have both, but this would be cost prohibitive (or hugely wasteful) with a SaaS vendor.

I’m going to circle back to Primary Function #4 because this a big reason folks choose a CDP vendor. …“My IT is backlogged; they can’t deliver in my required timeline; I want control”. All very likely true.

If I put my CMO hat on, I would find a consultant to architect the system. If done properly, this system would be a silo-buster and could help democratize A LOT of data throughout the org (see post on Data Silos here). Data/BI Analysts will go to town. Data Science can reap huge time savings. Many internal projects can spawn from a CDP; E.g., Marketing attribution. Endless possibilities, really.

Now, that then brings up the question of “Who’s budget?”. Ah, the joy of politics.

I will argue that the CMO should take this initiative on. They are the first and primary use-case. If I’m correct, that this will benefit multiple orgs, then that’s a big win for the CMO. That’s a CMO with enterprise-wide vision. That’s a future CEO.

In terms of time, there are many tools on the market that can be used to dramatically accelerate this project. In fact, I’ll put it out there, that with the right tools, this can be accomplished within several months.

If IT can’t handle it, I would consider starting with a consulting firm that can operate as a managed service, knowing that I can bring the resources in-house later, if that makes sense. This would be hosted in a virtual private cloud (and hopefully a solution would be flexible enough to not lock me into any one cloud vendor, either).

To conclude, if you don’t have a CDP project going, you’d be remiss if you didn’t get one going as soon as possible. But look inward first.