Our Addiction to Content is Killing Us

I’ve been writing this article in pieces during the last four years. It’s still incomplete. I’m publishing it in draft as I now realize I’ll be working on this until I die.

I was a content pusher

I’ve built integrations that cross shared, reposted, tagged and optimized content across multiple channels automatically. I had trackers on my phone and used a Fitbit. I logged, checked-in, tracked and rated. I was an early user of Exist.io and loved it (I still think their team is awesome).

From early in 2000 until roughly 2015, I tried to find every possible tool that could give me more reach. I saw social media as an optimization problem. If I could just get more content into more channels and get better analytics, I believed I wouldn’t need to do business development anymore. I’ve used Hootsuite, Buffer, Tweet Deck, ContentStudio. I played around with Contentful. I’ve scheduled, tweaked, tracked and enhanced.

At one point, I was even experimenting with LinkedIn, Facebook and Google ads. Going through the same process of tweaking, testing and pushing. Always trying to get better results and conversion.

I’ve spent much more time searching for, tweaking, testing tools that might give my content more reach then actually writing quality content. And, I’ve spent much more time trying to make business development unnecessary than it would have taken me to just meet and have coffees with enough people to have met all of my sales targets. Instead, I ended up spending twice as much time trying to ‘optimize’ the perfect workflow.

I was constantly testing new apps, linking them via tools like Zapier and IFTT. I was always looking for a way to streamline and enrich my data through more connections and a more seamless user experience. Around 2015, I did an audit on my LastPass account. I had more than 400 passwords for ‘business’ tools that I’d used once or twice.

The results seemed to justify the cost

And it worked. I got massive coverage and visibility. Everyone in the industry I was working in knew about me and my team. We dominated the social feeds and maintained a steady stream of content.

My ads converted and I could see a increase in views, clicks and conversion. It was expensive at scale but it worked. I got inbound conversions and calls. At the peak, my team spent 25% of their time feeding and maintaining this monster. We didn’t have any other choice. This was the game we had to play because we believed it was all-in or nothing. This was further re-enforced by the corporate narrative. Internally, we had targets and incentives to push more content and get more social media traction.

Beyond work, all the tracking gave me insights into my personal life. Where I went shopping, how long I slept, how much I ate during different times of the day and how active. I could see how productive I was when I listened to certain music and how the weather influenced my mood.

It was addictive and satisfying to check my heart rate and consider all the different stats and graphs the all the different apps provided. At work I spent my days tweaking and optimizing content streams and at home I was doing the same for my personal dashboards.

Until it didn’t…

With control of everything and insight into so much, I started to realize the cost. Costs that I hadn’t considered while setting up the tools and making the connections. Costs that weren’t clear in the pretty reports and buzzes and reminders to move and check-in.

The direct costs were easiest to see. All those little distractions meant less time focused on a conversation or a meeting. Less time to get lost in my children or a book. And anxiety. Needing to check-in, needing to relook at my activities and try something else. Have I completed the recommended tasks? Should I check again? Maybe I my GPS turned off yesterday and I lost a day of path data? Now many years later, I can look back at this time and see the same signs of early addiction that are common challenges within the Compulsion Loops of such games.

The indirect costs took me a long time to recognize:

  • The anxiety of needing to maintain a social content ecosystem (feed the beast), meant less time focused on real relationships.
  • The pressure on others in the team who often did feel their time was better spent talking with people rather than resharing, liking and discussing comments.
  • While each individual task or consideration took seconds, the aggregate time spent was massive. Especially when summed over the year.
  • The metric-driven approach to interactions meant that over time we became increasingly ambivalent towards human interaction. Everybody was a abstracted metric rather than a real person.
  • My life itself started to feel less meaningful. My days were full of ‘tasks’ without clear goals or alignment with values. My core objective in life seemed to be ‘more’.
  • All of that social traction actually dramatically included the junk in the feed. By giving the impression that I was reachable, responsive and connected, more and more people expected that I would be responsive to them. The overall flow into the top of the funnel increased, but the quality coming out the bottom decreased.
  • Doing the same amount of business with social media traction required more time than the same amount of business manually without all the social media noise.
  • Living healthily without the digital lifelogging was easier than doing it with all of the logging.

These concerns alone were enough for me to start slowly scaling back and removing tools, automations and making other tweaks.

Rediscovering privacy

I’ve thought privacy was a joke. Snowden showed us that even in the United States tracking is common. People have become products. We exchange our data for free services and convenience. I’m fine with that. I give you my data and you use it to make better products and services. But it isn’t really that way nor has it ever been.

Instead, it’s me granting the right for these companies to do anything with my data including things that I never even imagined might be possible. Data wholesalers and consolidators work to build detailed profiles of every person in the world to sell to other companies that do even more specific targeting and profiling for all kinds of different purposes. Even this is maybe okay.

Then what happens when these incredibly detailed profiles are stolen and used to target people for scams. Or published online exposing the habits and preferences of people to the world. Netflix went into detail on this whole area in the Social Dilemma.

Let’s try taking the extreme view that ‘sharing everything is better for society’. Sharing everything about everyone could lead to a world where people are more accepting of personal habits and quirks. Yet, even in such a world there is no governance or control of the accuracy of this consolidated data. No matter how progressive the world becomes, there will always be areas of taboo and crime that we all can agree we do not want to encourage (example: rape, murder, theft). So complete transparency of data without governance, creates a direct incentive for people to manipulate that date to punish and gain.

Preference data can easily put people in danger and ruin their lives. Imagine that some data consolidator decides (incorrectly) that you must be bankrupt because of the kind of searches and content. The service is hacked and your profile is exposed online. Searches for your name and address now produce a profile from a leading company that shows you as “likely bankrupt”. With such detailed information, eventually it will be stolen and it will be used to shame, extort, control or steal.

The laws are progressing too

The Singapore data protection act (PDPA) and the European general guidelines (GDPR) are good starts for digital governance. Global groups like MyData are also helping to lay the foundation for a more meaningful dialogue about data oversight and controls.

Yet with this progress, the relative monetary value of data continues to increase. Meaning that while there is increasing governance, there is increasing desire for companies to capitalize on data and hackers to steal it. The discussions at the recruiting company I worked for were an example of this. Whether GDPR or PDPA, the management always insisted — “Don’t worry. We can still do everything we have always done. Read the disclaimer on our website and our email signature, by giving us their personal data, we can do anything we want.” Yet I wondered, “Is that really what a reasonable person would expect when they send us their resume or CV?”.

Once I left that company and explored setting up my own firm, I started experimenting with different kinds of agreements and contracts where I attempted to explain how, why and what I was going to use data for. This was also an attempt for me to figure out my own views on data. Every conditional statement in the agreements left me feeling unsettled. “We will use your data for this and that and some other things.”

Eventually, the best answer was also the simplest. An absolute view that once you accept someone’s data, you should grant them absolute control and visibility on that data and how it is used. You should also only use that data for things that they have explicitly granted you rights to use it for and even the anonymous data collected must only be used in a manner that a ‘reasonable person’ would think acceptable.

At first this seems like an impossible task, yet in reality with centralised data storage and CRM systems, it’s amazingly easy to identify and manage all the stored records with any personal data for a given individual. It just took me to start thinking about how my systems should work not how they presently didn’t work.

There is more opportunity in isolated data then consolidated data

I never considered it at the time. Complete automation, streamlining, content pipelines, life logging, social sharing actually create less opportunity for meaningful work in the world.

Restrictions on data, force companies and individuals to invest in each other. If I can’t predict your buying behavior, I should invest more time in getting to know you.

Extreme automation is appealing as it tempts us with the ability to produce a perfectly controlled experience and result for the customer. Yet, in many areas, the best customer experience is having someone handle the process professionally, promptly and without trying to sell us something we don’t want.

Job seekers hate working with recruiters not because they don’t need the help or that a professional coach or recruiter couldn’t help them. Job seekers prefer to work with a real person from the company rather than a computer. Yet, these days if a job seeker has a choice of working with a recruiter who is going to lie and cheat them or an automated system, they will take the automated system.

Consider the restriction within GDPR that job seekers have the right to request manual screening of their profile. Since the emergence of computing, companies have tried desperately to automate away the recruiting and hiring process. This GDPR requirement forces companies to provide some kind of manual screening. Companies have a choice in how to respond to this requirement.

  • Avoid — ignore the requirement and continue to treat job seekers the same (semi automated and automated screening).
  • Outsource — work with a 3rd party to provide the manual screening service guaranteeing a low quality experience of the job seeker.
  • Build Expertise — see this as an opportunity to invest in professional coaching and counseling expertise internally. Treat job seekers as people. Respond to them professionally, give them advice and direction.

Imagine if a company like Google decided to spend on building a professional jobseeker consulting practice within Google. Every applicant gets a call. Every applicant gets a personal response. Making the recruiting process humane adds value across the entire business, yet requires completely rethinking the costs and approaches of traditional business functions that have been seen as opportunities for cost optimization.

Pressing Reset

After a few years experimenting with these approaches in my own company, I flipped the model completely. I stopped tracking all data for customers other than the most basic contact details and the emails they have sent me. I also set it up to clear all my records after five years.

During this time as I was figuring out what to do with my customer data, I also started to question my own data. I had thousands of Evernotes and Google Docs. I was registered with hundreds of sites and maintained multiple social media profiles. And I had no idea what data was where. It was too much, too complicated.

“What could I do?” I thought. All the data across so many different systems. So much data that wasn’t necessary. It had become a reinforcing cycle of wasted time. More tools, each one asking for just a few minutes of my time, multiplied; resulted in a strange kind of life — living within the compulsion loop.

In Greek Philosophy, we could see social media and online tools as appealing to our most Hedonistic tendencies. Focused on maximizing our emotional reactions to things and on encouraging short-term triggers, happiness and addiction.

So I started to delete.

I deleted:

  • Instagram
  • Snapchat
  • Skype
  • Line
  • Twitter
  • Multiple Google accounts
  • Multiple Microsoft accounts
  • Viber
  • Multiple LinkedIn accounts
  • Viedieo
  • Angel List
  • Yahoo
  • LibraryThing
  • Telegram
  • Fullcontact
  • Fitbit
  • Facebook
  • Quora (still migrating the better content to OneNote, OneDrive or Medium). I used a now defunct service ‘freemystuff.cc’ to do the data export. You can now directly request an export from Quora. How to Extract Your Data From Quora and Reddit | by Daniel Rosehill | Daniel’s Tech World | Medium
  • Hundreds of old websites (more than 30% had already gone offline) and I still have 300 old 1Password saved sites that I need to clear.
  • Next on my list is to full remove my Google accounts and my last remaining LinkedIn account. I will replace a personal ‘master’ LinkedIn account with one only linked to the company that I’m working with. When/if I leave that company, I will delete the LinkedIn account and start fresh at the next company.

Creating less ‘connected data’ and more ‘isolated single purpose data’

A big shift for me was disconnecting data and trying to make sure it is isolated within the area that it is being used for.

Whenever I work with a company, I keep only the files I need for my job (delete the rest) and save everything within the company-linked cloud accounts. At first this discipline took time and effort. Saving things to desktops and folders here and there is an easy escape. After more than a year, it has become habit and it feels weird doing otherwise.

I’m also exploring ways to download, encrypt archives older than 5 years so that when something I use is hacked, the data accessed is limited. For now, I’m just thinking to wipe data all data beyond 5 years.

I’ve entirely moved into the Office 365 environment. Partially because Microsoft has done an amazing job of making their tools seamless across desktop and cloud, but also because Microsoft Authenticator is an amazing 2nd factor authentication tool. I hope that Microsoft continues to build such great user-centric products after coming out of the valley of death.

I’m also building a frontend interface for the people and companies that I deal with so they can easily access, modify, delete or otherwise manage their data with complete visibility on how it is being used. For now this part is handled manually whenever anyone writes to me to check.

The last step will be an automatic wipe of data older than 5 years. So everyone will have the reassurance that their data isn’t retained beyond the period required by law.

Becoming Less

I feel more comfortable with my own data as I become less. And the data of those people I deal with as I collect less. Transparency is an inconvenience when systems are built to be opaque. When we start with a focus on transparency, it shapes the decisions we make and creates a better outcome for everyone.

Transparency also forces us to admit that much of that wonderful data we collect is self fulfilling. It helps us get more data which helps us get more data. All that data doesn’t help us have more meaningful interactions with other humans. Too much data does help us treat people as little ones and zeroes. Too much data also makes P-Hacking attractive and stifle real conversation because of fake evidence.

Sometimes we need to become less in order to become more.

Everywhere in society we see optimization problems taken to the extremes with unintended consequences. Rather than invest money in hiring more counselors, support and care professionals, we invest in facial recognition, remote policing and military style equipment for police.

Rather than invest in expertise we try to cheat. The solutions to our worlds challenges will not be found through increasing automation and predictive models. We already know what works. We just need to chose.

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Connor Clark-Lindh

Connor Clark-Lindh

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