Focus more on awesome work, than using the LinkedIn Resume Assistant

This week, I received the news telling me about LinkedIn’s Resume Assistant. At first, it didn’t bother me, but after a while, I returned to it. On one level I thought such a tool might be great for people starting their careers but then again not since you are basically copying what others have expressed. On another level, this makes me wonder about some bigger questions:

  • If you want to be unique and stand out from the crowd, using a template for resumes will probably not help you land your dream job since you will be hard to separate from others. You will just sound like all others in your field. Instead, I suggest you engage in what Anders Ericsson calls ‘deliberate practice’ meaning you will be so darn good that recruiters will contact you for that reason. Share your work from that practice, and people will recognize you.

 

  • The best recruiters are probably using far better methods to find unique talents, than just getting matches on LinkedIn searches. The best recruiters don’t care if you have all the exact words and expressions on your resume. Instead, they will notice you since you are good at sharing your knowledge from all your deliberate practice. If a recruiter contacts me, I would much rather hear that they do so since I seem awesome at what I do, rather than my resume matching their LinkedIn search.

 

Of course, there is nothing wrong with having an excellent resume. But the main value of the resume does not lie in the exact words you use to describe yourself. The main value lies in performing the hard work that needs to be done to reach excellence and then sharing that excellence through LinkedIn and other forums.

 

Photo by Brooke Cagle on Unsplash

Confused by Bitcoin? Me too. Here’s some guidance.

Bitcoin and other cryptocurrencies have me confused mostly. If someone asked me what it is, I would probably say something like: “It is a modern currency, distributed among people instead of banks and institutions, and people can get rich by investing in it”. But this, of course, doesn’t mean I understand what I am talking about.

Therefore, I started looking for other sources of guidance and found the following very helpful:

The ABC’S of Bitcoin and Everything You Need To Know About “Forks”, by James Altucher. A long article with all the ins and outs of what cryptocurrencies are.

Bitcoin makes even smart people feel dumb, by Scott Rosenberg at Wired. “Warren Buffett famously advised us never to invest in anything that we don’t understand. Bitcoin investors are paying Buffett no mind.”

Bitcoin vs Ethereum with Tuur Demeester, by Preston Pysh and Stig Brodersen at the Investors Podcast (We Study Billionaires). Preston and Stig talk to the cryptocurrency expert Tuur about how it really works.

So now, next time someone starts a conversation about Bitcoin, we all know a bit more about this mysterious complex mix of finance, engineering, and philosophy.

Culture, Machine Intelligence, and Ways of Working

As my followers know, I have written about the digital workplace for some years. Lately, however, I have grown somewhat tired of it: It seems we either only talk about the latest semi-smart upgrades in Office 365 and how they can be used, or some futuristic views of how we will work in 5 years from now. In one sense these are interesting subjects. In another sense, they are somewhat boring, repetitive, and distant. Some days, I couldn’t care less about the tools Microsoft throw at us, and how they relate to Slack. Meanwhile, I have started a blog on Machine Intelligence, and oh that has opened my eyes. Suddenly, I see more of the woods instead of just staring at the trees, and where we look is the deal breaker:

“Every man takes the limits of his own field of vision for the limits of the world.”
― Arthur Schopenhauer, Studies in Pessimism: The Essays

By expanding my field of vision, the limits of my world are moved further away. Then there are other writers who help me understand the world. One such example during the last months is Gloria Lombardi’s compilation of what she refers to as the future of work predictions for 2017. A line of smart people present their views on what they think will come this year, and here is my quick interpretation of the things the interviewees talk about:

 

Very short version: If you don’t take care of your employees and the exponential technology that is coming, the smart employees will leave and you will lose business deals while feeling left behind.

I have written and spoken about corporate culture before, and I have just entered the world of Machine Intelligence. Now I read more about the ways we organize work, including the Gig Economy which I honestly don’t see coming as fast yet but maybe it is. We should never think entrepreneurs are the only ones to save the world – the intrapreneurs are crucial here. Don’t underestimate the existing industrial companies.

So, let’s look at what Deloitte says about Machine Intelligence:

Collectively, these and other tools constitute machine intelligence: algorithmic capabilities that can augment employee performance, automate increasingly complex workloads, and develop “cognitive agents” that simulate both human thinking and engagement.

Exponential data growth is requiring Personal Knowledge Management for individuals, faster-distributed systems are democratizing information handling, and smarter algorithms help us process information to understand the world better. Combine these with the strong positive cultures we need, and the new ways we should trust the coworkers no matter where they are, and an interesting painting is forming. Trust me: Companies who miss this train, will for sure be left behind.

And on that note, we might as well focus on something important while working, and maybe this is the middle of the three rings: The purpose that the culture, machine intelligence, and ways of organizing work creates. The company I work for creates brakes and other safety equipment for large trucks and trailers. We all want them to stop instead of running into us, and we want them to be kind to the environment. We are also very focused on the culture we nurture and create, while keeping a close eye on the technology that is evolving. I think these are all keys to the great kinds of workplaces we look for.

If you think you lack a purpose, which is alarming since a purpose is the jet fuel in our tanks, you can always look at the upcoming possibilities. Just look at World Economic Forum which helps us zoom out and see the big picture, as in 5 global problems that AI could help us solve.

There is a lot of thought work left to be done from many people, to understand this. Thankfully, a lot of people are engaged in this, and I follow them closely.

How #PKMastery helped me create a blog on #AI

I have attended Harold Jarche’s Personal Knowledge Mastery (PKM) workshop twice, and they have been wonderful learning opportunities. There is a kind of meta-learning involved that I seldom experience otherwise: I learn about how I learn.

One of the images Harold uses to describe PKM is this

pkm

Image borrowed from Harold Jarche’s site

Harold describes PKM as:

PKM is a set of processes, individually constructed, to help each of us make sense of our world, work more effectively, and contribute to society. PKM means taking control of your professional development, and staying connected in the network era, whether you are an employee, self-employed, or between jobs.

  • Personal – according to one’s abilities, interests & motivation.(not directed by external forces)

  • Knowledge – understanding information and experience in order to act upon it.(know what, know who, know how)

  • Mastery – the journey from apprentice to disciplined sense-maker and knowledge catalyst.(masters do not need to be managed)

After talking about PKM at conferences and aiming to apply it at work, I am now applying it in a new blog. Since I work in the automotive industry, there are many trends and technologies within artificial intelligence (AI) that will affect us. This is a fascinating area to me, marrying the most human aspects with the most technical. To keep track of all the top news in this area, I created a blog called The Deckard Blog – named after the main character in Bladerunner. An example post can look like this:

23_ai_principles

The blog gathers what I think are the best AI news, quotes them, and then groups them into subject categories:

ai_categories

This way I can, based on my own interest in and fascination in a subject, Seek the most relevant news, Sense by categorizing it and explaining it, and Share by posting on the blog.

I will see where this adventure takes me, but at least I have taken the first step.