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.

Transcript

1. Hello !
2. Unicorns ARE PEOPLE TOO. Re-Thinking Soft and Hard Skills Liz Abinante • @feministy
3. 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
4. SOFT VS. HARD HIDDEN MEANINGS
5. SOFT VS. HARD A PROBLEMATIC DICHOTOMY
6. POTENTIAL ALTERNATIVE TERMS Robot by William Hollowell and Talking by Ed Gray from The Noun Project
7. REAL PEOPLE TIPS FOR TEACHERS, INTERVIEWERS & MANAGERS
8. SOFT & HARD A problematic dichotomy.
9. WHAT ARE SOFT SKILLS?
10. communication friendliness team building influence persuasion conflict resolution
11. PROJECT, TEAM, AND TASK MANAGEMENT. communication friendliness team building influence persuasion conflict resolution
12. MANY EMPLOYERS ACTIVELY SEEK OUT SOFT SKILLS IN PROSPECTIVE EMPLOYEES, MAKING THEM NEAR REQUIREMENTS FOR SUCCESS IN THE WORKFORCE.
15. BUT IF SOMETHING IS A NEAR REQUIREMENT, WHY ARE WE DESCRIBING IT AS “SOFT”?
16. SOFT ! EASY TO MOLD, CUT, COMPRESS, OR FOLD; NOT HARD OR FIRM TO THE TOUCH
17. SOFT ! HAVING A PLEASING QUALITY INVOLVING A SUBTLE EFFECT OR CONTRAST RATHER THAN SHARP DEFINITION
18. mushy dim lenient easy goingcompassionate subdued silky gentle forgiving tolerant
19. mushy dim lenient easy goingcompassionate subdued silky gentle forgiving tolerant
20. “SOFT” IMPLIES THAT IT IS LESS IMPORTANT BY USING A WORD THAT ALSO MEANS THINGS LIKE “GENTLE”, “DIM”, AND “PLEASING.”
21. I AM NOT A STUFFED ANIMAL. ! I AM NOT A CHEESE OR A FLUFFY PILLOW
22. I am a person who likes working with other people.
23. WHAT ARE HARD SKILLS?
24. programming computation physical labor statistical analysis
25. HARD ! SOLID, FIRM, AND RESISTANT TO PRESSURE; NOT EASILY BROKEN, BENT, OR PIERCED.
26. HARD ! REQUIRING A GREAT DEAL OF ENDURANCE OR EFFORT.
27. resistant solid unyielding arduous grueling strict severe violentaustere reliable rigid
28. resistant solid unyielding arduous grueling strict severe violentaustere reliable rigid NOPE. No by Naomi Atkinson from The Noun Project
29. THESE SYNONYMS SOUND MORE LIKE A LIST OF PERSONALITY TRAITS FROM A DATING SERVICE THAN A LIST OF JOB REQUIREMENTS.
30. MY SKILLS ARE NOT VIOLENT, THEY ARE NOT STRICT OR SEVERE.
31. It is not grueling to write code.
32. WRITING CODE IS MENTALLY CHALLENGING AND REQUIRES TRAINING AND TOOLS.
33. OUR TOOLS ARE WRONG. ! THEY DON’T MEAN WHAT WE THINK THEY DO. WE ARE FORCED TO INFER MEANING. Tools by Jeremy J Bristol from The Noun Project
34. WE CAN INFER ALL WE WANT, BUT ! OUR TOOLS ARE BROKEN. Broken Light Bulb by Gregory Sujkowski from The Noun Project
35. WE STRUGGLE WITH SKILLS THAT DON’T FIT INTO A PERFECT BOX.
36. Code reviews are nebulous.
37. A GOOD CODE REVIEW TAKES SOFT AND HARD SKILLS. ! THEY REQUIRE TECHNICAL KNOW-HOW AND SUBJECTIVE, CONSTRUCTIVE ANALYSIS.
38. SURPRISE!
39. SURPRISE! COMMUNICATION PROBLEMS HAPPEN. A LOT.
40. WE NEED TO MAKE NEW TOOLS. Broken Light Bulb by Gregory Sujkowski from The Noun Project
41. Speaking of tools…
43. 483 JAVASCRIPT FRAMEWORKS
44. wtf...?
45. THIS IS BULL !
46. We can build better.
47. WE CAN’T THROW EVERYTHING AWAY, THOUGH. ! SORRY!
48. HUMANS LIKE BLACK & WHITE.
49. DICHOTOMIES MAKE THE WORLD EASIER TO PARSE. ! WELL, WE LIKE TO THINK THEY DO.
50. DICHOTOMIES HELP US MENTALLY AUTOMATE INTERPERSONAL INTERACTIONS.
51. AUTOMATION IS GREAT! WE LOVE AUTOMATION!
52. BUT
53. AUTOMATION SHOULD BE USED WISELY, NOT INDISCRIMINATELY.
54. POTENTIAL ALTERNATIVES We can do better than this, folks.
55. WHAT ARE WE ACTUALLY TRYING TO DESCRIBE?
56. SOFT SKILLS ! INTERPERSONAL SKILLS PERSONALITY TRAITS TASK- & MANAGEMENT-RELATED SKILLS CUSTOMER-FACING SKILLS
57. interpersonal human subjective psychological personal rational cognitive social life-learned
58. HARD SKILLS ! CERTIFIED, TESTABLE, OR MEASURABLE KNOWLEDGE AND THE ABILITY TO USE THAT KNOWLEDGE
59. quantifiable technical professional academic specialized computational robot learned mechanical book-learned
60. PAIRED ALTERNATIVES
61. QUANTIFIABLE INTERPERSONAL Calculator by Luboš Volkov from The Noun Project SKILLS ARE MEASURABLE OR IMMEASURABLE.
62. TECHNICAL PSYCHOLOGICAL Brain by Martha Ormiston from The Noun Project MENTAL EFFORT IS REQUIRED FOR BOTH.
63. BOOK-LEARNED LIFE-LEARNED GAINED THROUGH PRACTICE VS. TRAINING.
64. ROBOT HUMAN HUMANS ARE INDIVIDUALS.
65. TECHNICAL SOCIAL TOOLS REQUIRED FOR BOTH TYPES.
66. REAL PEOPLE Adjusting expectations and action steps.
67. T PS Alert by deadtype from The Noun Project
68. TEACHERS & MENTORS
69. 1 TEACH ETHICS MODEL SOCIAL SKILLS
70. 2 REWARD PROGRESS CORRECT MISSTEPS
71. 3 PROVIDE FEEDBACK & CONSTRUCTIVE CRITICISM DURING THEIR LEARNING PROCESS
72. INTERVIEWERS & HIRING MANAGERS
73. 1 ASK A LOT OF QUESTIONS ABOUT INTERPERSONAL SKILLS AND THEIR EXPECTATIONS FOR THE ROLE.
74. SAMPLE QUESTIONS
75. WHAT ROLE DO YOU PLAY BEST ON A TEAM? ! DESCRIBE A GOOD CODE REVIEW. ! WHEN YOU PAIR, DO YOU PREFER TO DRIVE OR NAVIGATE?
76. WHAT LEVEL OF FEEDBACK DO YOU EXPECT FROM YOUR MANAGER? YOUR PEERS? ! WHAT TYPE OF FEEDBACK IS MOST VALUABLE? ! HOW DO YOU LIKE TO WORK? ALONE? IN A PAIR?
77. 2 INFORM THEM OF EXPECTATIONS AND WHY YOU VALUE INTERPERSONAL ABILITIES.
78. 3 ADJUST EXPECTATIONS OF THEIR ROLE WITHIN THE COMPANY AND ON THEIR TEAM.
79. MANAGERS & TEAM LEADS
80. THIS IS A LOT OF WORK. BUT IT’S WORTH IT. PROMISE!
81. 1 COLLABORATIVELY CHANGE JOB DESCRIPTIONS WITH HELP FROM DIRECT REPORTS, UPPER MANAGEMENT, AND HR. Chameleon by Radu Luchian from The Noun Project
82. 2 PROVIDE TRAINING: PAIR PROGRAMMING, FEEDBACK, AND CODE REVIEW WORKSHOPS. Teacher by Jaclyne Ooi from The Noun Project
83. 3 MAKE OPPORTUNITIES FOR NEW LEADERS ON SMALL PROJECTS AND FOR PAIR PROGRAMMING TO REINFORCE NEWLY LEARNED SKILLS.
84. 4 GIVE FEEDBACK FREQUENTLY WITH REGULARITY AND SPONTANEITY.
85. IT’S EASY TO BE A UNICORN. Unicorn by caba kosmotesto from The Noun Project
86. IT’S HARD TO BE A PERSON.
87. Bye ! Liz Abinante • @feministy • me@liz.codes This slide is tan at the request of my RailsGirls Summer of Code intern, who also picked out my outfit.