Unicorns Are People, Too: Re-Thinking Soft and Hard Skills

As developers, we tend to value hard skills that can be quantified or measured objectively. Job postings search for unicorns, but we are people first and foremost and being human isn't as easy as programming. While the code comes easily, the soft skills that make us human are complicated and difficult to get right. This talk will explore the danger of neglecting so-called "soft" skills, what we stand to lose by overvaluing technical skills, and alternatives to the hard and soft dichotomy.

Presented at Open Source Bridge 2014 in Portland, Oregon

Transcript

1. Unicorns ARE PEOPLE TOO. Re-Thinking Soft and Hard Skills Liz Abinante • @feministy
2. SOFT VS. HARD WHAT ARE SOFT AND HARD SKILLS? Cheese by Consuelo Elo Graziola, Pillow by Yazmin Alanis, Hard Hat by André Renault, and Mountains by Cris Dobbins from The Noun Project
3. SOFT VS. HARD HIDDEN MEANINGS Cheese by Consuelo Elo Graziola, Pillow by Yazmin Alanis, Hard Hat by André Renault, and Mountains by Cris Dobbins from The Noun Project
4. SOFT VS. HARD A PROBLEMATIC DICHOTOMY Cheese by Consuelo Elo Graziola, Pillow by Yazmin Alanis, Hard Hat by André Renault, and Mountains by Cris Dobbins from The Noun Project
5. POTENTIAL ALTERNATIVE TERMS WE CAN DO BETTER THAN THIS. Robot by William Hollowell and Talking by Ed Gray from The Noun Project
6. REAL PEOPLE TIPS FOR TEACHERS, INTERVIEWERS, AND MANAGERS
7. Soft HARD A problematic dichotomy. &
8. WHAT ARE SOFT SKILLS?
9. communication friendliness team building influence persuasion conflict resolution
10. PROJECT, TEAM, AND TASK MANAGEMENT. communication friendliness team building influence persuasion conflict resolution
11. MANY EMPLOYERS ACTIVELY SEEK OUT SOFT SKILLS IN PROSPECTIVE EMPLOYEES, MAKING THEM NEAR REQUIREMENTS FOR SUCCESS IN THE WORKFORCE.
12. BUT IF SOMETHING IS A NEAR REQUIREMENT, WHY ARE WE DESCRIBING IT AS “SOFT”?
13. Soft easy to mold, cut, compress, or fold; not hard or firm to the touch. ! having a pleasing quality involving a subtle effect or contrast rather than sharp definition.
14. mushy dim lenient easy goingcompassionate subdued silky gentle forgiving tolerant
15. mushy dim lenient easy goingcompassionate subdued silky gentle forgiving tolerant
16. “SOFT” IMPLIES THAT IT IS LESS IMPORTANT BY USING A WORD THAT ALSO MEANS THINGS LIKE “GENTLE”, “DIM”, AND “PLEASING.”
17. I AM NOT A STUFFED ANIMAL. I AM NOT A CHEESE. I AM NOT A FLUFFY PILLOW. ! I AM A PERSON WHO LIKES WORKING WITH OTHER PEOPLE.
18. WHAT ARE HARD SKILLS?
19. programming computation physical labor statistical analysis
20. HARD solid, firm, and resistant to pressure; not easily broken, bent, or pierced. ! requiring a great deal of endurance or effort.
21. resistant solid unyielding arduous grueling strict severe violentaustere reliable rigid
22. resistant solid unyielding arduous grueling strict severe violentaustere reliable rigid NOPE. No by Naomi Atkinson from The Noun Project
23. THESE SYNONYMS SOUND MORE LIKE A LIST OF PERSONALITY TRAITS FROM A DATING SERVICE THAN A LIST OF JOB REQUIREMENTS.
24. MY SKILLS ARE NOT VIOLENT, THEY ARE NOT STRICT OR SEVERE. IT IS NOT GRUELING TO WRITE CODE. ! IT IS MENTALLY CHALLENGING AND REQUIRES TRAINING AND TOOLS.
25. WRONG. OUR TOOLS ARE Tools by Jeremy J Bristol from The Noun Project THEY DON’T MEAN WHAT WE THINK THEY DO. WE ARE FORCED TO INFER MEANING.
26. BROKEN. OUR TOOLS ARE Broken Light Bulb by Gregory Sujkowski from The Noun Project WE CAN INFER ALL WE WANT, BUT
27. A PERFECT BOX. THAT DON’T FIT INTO WE STRUGGLE WITH SKILLS
28. AND SUBJECTIVE, CONSTRUCTIVE ANALYSIS. THEY REQUIRE TECHNICAL KNOW-HOW CODE REVIEWS ARE NEBULOUS. A GOOD CODE REVIEW TAKES SOFT AND HARD SKILLS.
29. HAPPEN A LOT. PROBLEMS COMMUNICATION
30. TOOLS. WE NEED TO MAKE NEW
31. Potential ALTERNATIVES We can do better than this, folks.
32. WHAT ARE WE ACTUALLY TRYING TO DESCRIBE?
33. Soft INTERPERSONAL SKILLS PERSONALITY TRAITS TASK- AND MANAGEMENT-RELATED SKILLS CUSTOMER-FACING SKILLS
34. interpersonal human subjective psychological personal rational cognitive social life-learned
35. HARD CERTIFIED, TESTABLE, OR MEASURABLE KNOWLEDGE AND SKILLS RELATED TO USING THAT KNOWLEDGE
36. quantifiable technical professional academic specialized computational robot learned mechanical book-learned
37. PAIRED ALTERNATIVES
38. QUANTIFIABLE Interpersonal Calculator by Luboš Volkov from The Noun Project Emphasizes that skills are measurable or immeasurable.
39. TECHNICAL Psychological Brain by Martha Ormiston from The Noun Project Gives value to mental effort required for both skill sets.
40. BOOK-LEARNED Life-Learned Distinguishes between practice and training.
41. ROBOT Human Values human interactions and individuality.
42. MECHANICAL Social Signals that tools are required for both types of skills.
43. Real PEOPLE Adjusting expectations and action steps.
44. T PS Alert by deadtype from The Noun Project
45. TEACHERS & MENTORS
46. TEACH ETHICS MODEL SOCIAL SKILLS
47. REWARD PROGRESS CORRECT MISSTEPS
48. INTERVIEWERS & HIRING MANAGERS
49. ASK A LOT OF QUESTIONS ABOUT INTERPERSONAL SKILLS AND THEIR EXPECTATIONS FOR THE ROLE.
50. INFORM THEM OF EXPECTATIONS AND WHY YOU VALUE THESE ABILITIES.
51. ADJUST EXPECTATIONS BOTH WITHIN THE COMPANY AND ON THEIR TEAM.
52. MANAGERS & TEAM LEADS
53. THIS IS A LOT OF WORK. BUT IT’S WORTH IT. PROMISE!
54. COLLABORATIVELY CHANGE JOB DESCRIPTIONS WITH DIRECT REPORTS, UPPER MANAGEMENT, AND HR. Chameleon by Radu Luchian from The Noun Project
55. PROVIDE TRAINING Teacher by Jaclyne Ooi from The Noun Project PAIR PROGRAMMING, FEEDBACK, AND CODE REVIEW WORKSHOPS.
56. MAKE OPPORTUNITIES FOR NEW LEADERS ON SMALL PROJECTS AND FOR PAIR PROGRAMMING TO REINFORCE NEWLY LEARNED SKILLS.
57. GIVE FEEDBACK FREQUENTLY WITH REGULARITY & SPONTANEITY
58. IT’S EASY TO BE A UNICORN. Unicorn by caba kosmotesto from The Noun Project
59. IT’S HARD TO BE A PERSON. Person by Jennifer Cozzette from The Noun Project
60. Bye! I’M LIZ. I’m a person (not a unicorn) and I like friends! Liz Abinante • @feministy • eabinante@gmail.com