Probably the best writing advice to date

I’m in the final sprint to finish the first draft of my book in the next four weeks which means I’m ignoring pretty much everything else. Except Twitter.

I’ve struggled all day, every day to ignore Twitter since I started writing this book back in October. I’ve failed on that pretty much every day. Though, I have reduced my addiction to my carefully curated information hose. I wonder how much more quality procrastination writers had before Twitter.

Sometimes though Twitter comes through and delivers something so helpful and timely that I’m reminded for all the reasons I love this site over any other.

Behold the best advice on writing ever:

I’ve had three mantras to get me through the first draft:

finished not perfect

the purpose of the first draft is for it to exist

let the editor sort this out

Those mantras help me with the writing process. They keep me moving forward.

But Ava’s advice validated all the feels that happen when you see your raw, messy thoughts masquerading as a future book.

I screenshotted her tweet and read it every day right now as I push towards the finish.

Share it with anyone you know who writes.

This podcast about Magic the Gathering gave me all the feels

Never thought I’d write something like that. But this 99% Invisible episode on the storytelling and design that goes into making this epic card game (and fanbase) is absolutely fascinating. Magic the Gathering folks get a lot of shit for their fandom and obsession with fantasy worlds. This podcast takes you deeper into the game, covering strategy and the people whose day jobs involve building these worlds. It’s really well done.

Most people might skip this topic. But that’d be a mistake.

Give it a listen.

 

(def not how to play Magic)

Hey career services, you all ok over there?

Seriously. How you doing career services? Hanging in there?

I ask because things are looking a bit rough. And I’m worried about you guys. I just read a summary from  NACE’s 2018 Student Survey on the resources students use most in the full time job search. The numbers are bleak.

NACECareerServices

Source: NACE, The Job Search Resources Students Use, Find Most Useful

Yiiiiiikes. Only 26.2% of students found career fairs helpful, 9% for virtual career fairs. Career services puts in a ton of work for these events and students are like,

Only 20% of students surveyed found employer presentations useful. Same for having employer reps on campus. Both resources takes a tremendous amount of coordination and logistics in career services.

Alumni relations touts the benefits of connecting current students with alumni but alumni-as-a-job-search-resource didn’t do much better. Only 15% of students found alumni useful.

But the worst bit is that 50.3% of students considered company websites useful in the job search while only 21.6% considered the career center useful.

Ouch.

If students find company websites more helpful than the entirety of resources and people within career services, then what is the goal of career centers?

With this kind of data it’s pretty clear career centers need to change things up. And that probably feels like an overwhelming task right now.

I know you guys work your faces off. You’re underfunded and understaffed. After being the department that was ignored for years, all eyes are on your department because now you’re suddenly responsible for all the outcomes. As a former university MBA career coach, I worked in a system that valued outcomes above all else. In MBA land outcomes = rankings and rankings > everything else. Tying your work to student outcomes with metrics defined by outsiders doesn’t make change any easier. In fact, it makes it harder.

But just because it’s hard doesn’t mean you can’t, and shouldn’t, change it up. Those numbers don’t lie. Students don’t find value in what you’re offering.

I’ve had plenty of positive, passionate conversations with many of you who are bursting with ideas to change the status quo in university career centers. I know that many of you feel limited in your ability to make change happen.

So here’s my advice to you, the career services professional who has refreshing, bold, impactful, fabulously bad ass ideas that will transform career services for the better: make it happen in 2019.

Wait, wait. Let me rephrase.

Here’s what I want you to do:

Go rogue, break the all the damn rules. 

Here’s how to do that:

  • Ask for forgiveness not permission.
  • Don’t wait for leadership to change things. Change begins with you.
  • Apply for leadership roles even if you’re not qualified. Push through personal doubt.
  • Pitch radical presentations and workshops for every single university career services conference. If they don’t accept yours host a webinar at your school or for your personal network instead.
  • Actually, host a webinar anyway on the subject anyways. You’ll learn valuable marketing and public speaking skills in the process.
  • Join the conference committee for your regional or national career center conference. Vote for radical presentations from underrepresented voices.
  • Listen to and lift up underrepresented voices in the industry. Change and new ideas come from diversity of perspectives and experience.
  • Apply for board openings at national university career organizations. Challenge outdated ideas.
  • Experiment with new workshops and coaching methods (even if its your first year on the job).
  • Host a design thinking workshop to get better ideas into your department. Then execute on them.
  • Question the status quo. Ask why. Keep asking why.
  • Find your power squad. Find the people who ask why, who challenge the status quo. Get inspired. Then build something together.
  • After you build it, reflect. What worked? What will you do differently next time?
  • Strive for impact not outcomes.
  • Measure your impact. Then promote the shit out of your success. Don’t expect others to notice.
  • Make a list of every.single.resource and workshop your department offers. Then ask why. “Why career fairs? Why resume reviews?”
  • Then ask how. “How might we do this instead?”
  • Every time your department or leadership claims they are innovating, ask how. Then ask what makes those initiatives innovative.
  • Get students involved. Ask them what they need.
  • Better yet, give them a budget and support to create a program they need so they get experience creating and collaborating.
  • Stop looking for ideas at elite schools and in departments with all the money. Instead, look at all kinds of institutions for new ideas (especially community colleges)
  • Get to know recent alumni (ignore alumni relations – reach out on LinkedIn personally). Interview them. Translate alumni insights and experiences nto new initiatives.
  • Learn about new hiring algorithms and how they’re making old school career advice obsolete.
  • Upskill regularly.
  • Take an online course in change management to learn how to influence change.
  • Commit to chaos in 2019.

Disrupt is an overused phrase. But career services needs to change and change fast. If students get more value out of a company website than they do your center, things are really not ok in career services.

So to my fellow career coaches who are nodding their heads along to this article, bursting with ideas: go forth and create chaos. Wreck the status quo. Challenge your leadership. Become the new leadership.

Commit to chaos in 2019.

Your students will thank you.

Understanding hiring algorithms: Career coaching in 2019

Today, hiring technology vendors increasingly build predictive features into tools that are used throughout the hiring process.They rely on machine learning techniques, where computers detect patterns in existing data (called training data) to build models that forecast future outcomes in the form of different kinds of scores and rankings.”  Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias

The hiring process is changing faster than most realize. Automated tools that use machine learning to source, analyze, and rank candidates are already integrated into the hiring process, sometimes without candidates knowing it. As we move into 2019, the adoption of predictive hiring tools show no sign of slowing down.

Career coaches and university career services departments have a responsibility to understand these hiring algorithms and their impact on job seekers. They need to create new strategies and update career workshops to help job seekers navigate hiring algorithms. (spoiler alert: my career workshops cover this)

If you don’t work in tech, artificial intelligence and machine learning can seem like intimidating topics. Even more unhelpful, hiring algorithms are a bit of a black box. The transformation to an automated hiring process is happening behind the scenes. It’s hard to figure out which companies use this technology and exactly these tools work. It’s challenging to know which automated tools use questionable data or cement bias into the hiring process.

Luckily, there’s a new report out to help career coaches get up to speed on new HR technology and hiring algorithms. The report, Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias,is produced by the nonprofit Upturn. Upturn’s mission is to promote “equity and justice in the design, governance, and use of digital technology.” Their mission shines through in their new report.

The report offers career coaches a comprehensive review of new hiring technology. The report is well-written, making it an accessible read. More importantly it isn’t filled with marketing promises that dominate HR tech press. Instead, it dives deep into the issues and impacts that hiring algorithms can have on the hiring process. The report covers the ways in which bias can be baked into hiring algorithms. It’s a refreshing piece of content in a sea of HR tech press that relentlessly praises new hiring technology as efficient and transformative, often ignoring the impact on the candidate.

Honestly I could fill this post with quotes from the report. But I’ll stick to these two bits from the executive summary. If you don’t have the time to read the report, at least read the executive summary. Then carve out 30 minutes to read the rest before 2019. Consider this your last professional development activity of 2018.

Hiring is rarely a single decision point, but rather a cumulative series of small decisions. Predictive technologies can play very different roles throughout the hiring funnel, from determining who sees job advertisements, to estimating an applicant’s performance, to forecasting a candidate’s salary requirements.

Hiring tools that assess, score, and rank jobseekers can overstate marginal or unimportant distinctions between similarly qualified candidates. In particular, rank-ordered lists and numerical scores may influence recruiters more than we realize, and not enough is known about how human recruiters act on predictive tools’ guidance.

After you read the report, go further, and read How to learn about ML/AI as a non tech person.

Remote jobs are going to be hot hot hot in 2019

In 2017, 43% Americans worked remotely during part of their work week. That was up from 39% in 2012. With the proliferation of remote job boards and a flood of digital nomad lifestyle pics on Insta, it’s no wonder people are getting curious about remote work. The days of sketchy Craigslist WFH jobs are over. 

Just looking through the perks and benefits of remote work makes me wonder why anyone is going into work on a regular basis. Some of these fully remote companies have better workplace perks than traditional workplaces.

Remote work isn’t just for programmers. There are plenty of opportunities for people outside of tech to work remotely. Take a look:

I’m on a mission to get people to experiment more with their careers. So I’m teaching people how to get a remote job in 2019. My online course, How to Get a Remote Job, opens in February.

Lazy blogging with Twitter

I originally joined Twitter because it was the perfect form of lazy blogging. I could put articles I was reading out into the world with short commentary. No full blog post needed. Now I write more and Twitter feeds what I write about. Despite the fact that Twitter is dumpster fire, I love it, massively.

This book writing thing is messing up my ability to write here regularly. So now I will use my favorite site for lazy blogging as the content for future lazy blog posts here.

My most favorite Twitter finds for the week. I tend to share posts on higher education, international education, and artificial intelligence.

Community colleges are full of innovation and teaching skills for career changers. Traditional universities should look to them for more inspiration:

This quote rang so true in the midst of reports about hunger insecurity on campus:

Again more smart thinking from community colleges:

In AI news, European checkpoints are going to use microexpressions to figure out if you’re lying. If I were writing a full post I’d research whether or not it’s based on the same tech HireVue uses when analyze candidate’s video interviews.

Also the AI Now Institute (an organization that I am majorly crushing on and want to work for) released their AI Now 2018 Report which presents 10 recommendations for navigating artificial intelligence technology. Everyone should read it. This isn’t the future. This is the reality now.

More on the wild wild west of AI hiring.

And lastly, any politician who sponsored this could count on the millennial vote. One can dream.

 

 

Could machine learning replace career coaches?

Buried at the bottom of an an HBR post titled 8 Ways Machine Learning is Improving Company Processes, is a little nugget about the ways machine learning might soon affect career planning. Machine learning could help employees in navigate their career development by providing:

Recommendations (that) could help employees choose career paths that lead to high performance, satisfaction, and retention. If a person with an engineering degree wishes to run the division someday, what additional education and work experience should they obtain, and in what order?

Could this be a career coach in the future of work? It’s a fascinating idea and I’d love to see it in practice. We’ve already seen machine learning technology take over some parts of a career advisors job. There’s even a chatbot in development that’s trying to be a career coach (let’s hope they’re better than LinkedIn’s mediocre job recommendation algorithm.) IBM uses AI to guide job seekers through their search.

A good career coach will listen to you, help you work out ideas, guide you through an ambiguous process, support you emotionally, and reflect your own words back to you. Machine learning technology can’t do this yet, in answer to my clickbait title.

But there aren’t enough good career coaches to go around. And few people can even afford a good career coach. Moreover, not every organization offers career coaching that helps employees navigate their next steps. Tools that help people navigate a world full of increasingly ambiguous career paths are mighty helpful.

Like many jobs, career coaches won’t be fully replaced by robots or artificial intelligence anytime soon. There will always be people who prefer working with people over machines. But the role of career coaches will change as new tools and technology emerge. Career coaches need to be aware of these changes. The workplace and available roles are shifting rapidly. Career coaches need to be able to coach their clients through these changes. They need to rethink outdated career advice, especially given that our job search is becoming less human. University career departments in particular need to upskill.

Today’s post is brought to you by my half way mark to 50K words for #NaNoWritMo. I’m deep into a chapter on the future of work for my book and still finding a ton of good content to write about. The challenge of course is to write about it and not just read about it. Reading is not writing, I have to remind myself a bajillion times a day.

If you’re into this type of stuff, subscribe and I’ll send you things about careers, future of work, and probably a bunch of gifs.

Where’s the discussion about employee privacy in the future of work?

In the age of big data, a measure-everything mindset is emerging. Julia Ticona, a sociologist and researcher with the Data and Society think tank in New York, says that the same types of apps that track and keep tabs on restaurant workers or delivery people 24/7 are now migrating to white-collar jobs.

But while service and manufacturing industry workers are more used to overt productivity measurements, such systems are often sold to office workers as opportunities to maximize their own productivity, she explains. “For lower wage folks, it’s about scheduling and hours,” says Ticona. “For the white collar folks, it’s about being the ‘best you.’” The inevitable future of Slack is your boss using it to spy on you

There’s so much in this article about all the ways your employer uses new technology and invasive data collection techniques to spy on you at work.  There’s even an example of a company that tracks their employees outside of work hours. Your workplace is creeping ever closer to the Circle.

So much of the future of work is focused on robots taking our jobs. But that discussion overlooks much of what’s happening outside of robots, mainly the erosion of employee privacy. The idea that companies should have the rights to all data an employee produces in the course of their workday is absurd. Employee surveillance shouldn’t be normalized. Moreover, we need more discussion about the people making decisions about what constitutes worker productivity. Who are they and how are they qualified to make these decisions? You can bet the executives and upper management aren’t being tracked like this.

I disagree that this is all inevitable. We have the power to say no to it. We have the power to teach emerging leaders how to not to use this technology or point out the potential for abuse. Employee privacy shouldn’t be a trade off for a paycheck. Employees have the power to ask questions: How are you using my personal data? What data are you monitoring? What assumptions are you making about my work when you build productivity measuring algorithms?” 

Future employees have the power to ask the right questions during their job interviews. Let’s start teaching people the right questions to ask in an interview for a white collar role. How do you measure success in this role? How do you track worker productivity? How much data do you collect on your employees and what do you use it for?

We’re in the middle of a massive transition to a quantified workplace where leadership wants to measure everything in the pursuit of pure productivity. The people who are impacted most under this system must participate in shaping this transformation and pushing back.

employee privacy

#NaNoWriMo is wrecking my blogging schedule

I’m deep into National Writing Month (#NaNoWriMo) and it’s wrecking my ability to write here. I’m in the middle of writing my second book and so far, I’m 14,000 words in for the month of November. For context, I wrote 9,000 words in all of October. The goal of #NaNoWriMo is to write 50,000 words. I’m a little behind but I’m still shooting for it.

It’s also International Education Week (IEW2018) so I’m busy promoting GlobalMe School and teaching career services how to improve international student career outcomes on one of my other websites. In short, I’m tapped out of words.

On the plus side, #NaNoWriMo month is an excellent tool for aspiring book writers. Things I’ve learned in only two weeks:

  • The only way you will write a book is to put your ass in a seat and write. Truth.
  • Writing without self-editing is the hardest part of this month long exercise. I’ll never make it to 50K words if I edit.
  • Researching writing is not writing your book. Neither is writing about writing a book (which I’m doing now). Writing your book is the only writing that counts towards the goal of publishing a book.
  • Getting comfortable with the rawness of your words and accepting the messiness is part of the process.
  • The world is full of people who say they can write better than (insert book here). Like most things, it’s so much harder than it looks.

So in lieu of a post, here’s an article dump on the most interesting things I’ve read this week about AI and ethics, a subject I’m increasingly more interested in. If I weren’t so brain dead from barfing words elsewhere, I’m sure I’d come up with something clever to say about these. But I can’t. So here we are.

The Newest Jim Crow

Principles for Ethical Machine Learning

China takes facial recognition tech to Africa

This insanely creepy roundup of patents to increase corporate surveillance in your home and I can’t even…

Followed by this tweet by the ever insightful researcher Zeynep Tufekci.