Decisions, Decisions, Decisions Thomas S. Krieshok University of
Decisions, Decisions, Decisions Thomas S. Krieshok University of Kansas [email protected] Key Points: The human brain is not designed for happiness When we try to predict what will make us happy, we make errors Implications of this for career counseling
Members of the A (Adaptability) Team over the years: Chris Ebberwein Mike Black Robyn McKay Rich Scott Melanie Noble
Selby Conrad Shawn Bubany Brian Cole John Jacobson Craig Beeson Kate Sirridge
Kristin Rasmussen Maggie Syme Sarah Brown Mary Krogmann Matt Robinson Dan Cox
Eric Lyche Jeff Rettew Rhea Owens Thomas Motl Abby Bjornsen Wendy Shoemaker
Matt Davis Carrissa Huffman Kirsten Wells Michael Rosen Benjamin Rutt Alex Vuyk
Aaron Gates Brittany Stewart Erik Clarke Craig Warlick Marlon Beach Cherie Oertel
Michael Ternes Jamie Kratky Paul Ingram Meg Givens Aaron Van Gorp Not designed for happiness
Humans not designed for Happiness, but Survival and Reproduction We always want just a bit more wealth, privilege, beauty, and youth Precursors to survival and reproductive likelihood The Hedonic Treadmill Not designed for happiness The human mind as an experience simulator
We are not so adept at predicting the intensity and duration of our future emotional reactions Affective Forecasting (Wilson & Gilbert) Side Effects of human design 1. We overestimate our ability to get things done in the future 2. We underestimate our resourcefulness for dealing with obstacles
3. Consciousness only sees a movie about reality Side Effects of human design Leads to Miswanting We think something will make us happier than it does ...and based on faulty assumptions, We avoid things we expect will be difficult
Side Effects of human design So we want things we won't end up liking And we resist wanting things we would end up liking Doing better but feeling worse (Iyengar, Wells, & Schwartz) College seniors: Maximizers vs. Satisficers
Perceived value of possible outcomes influenced by: Mis-predicted expectations during the decision process Affect experienced during the decision process itself Social values Doing better but feeling worse (Iyengar, Wells, & Schwartz) Even when they get what they want-Maximizers may not want what they get
Human Design Issues The brain is part of the problem Areas for Wanting Areas for Liking Human Design Issues Amalgam of brain systems Cobbled together over time To adapt to evolving environmental demands System 1 and System 2
System 1: Intuitive, non-conscious mind -related to older functions of the brain System 2: Rational, often conscious mind -related to newer functions of the brain -especially language T h e T w o - S y s te m V i e w T h e d is tin c tio n b e tw e e n in tu itio n a n d re a s o n in g h a s b e e n a
to p ic o f c o n s id e ra b le in te re s t in th e in te rv e n in g d e c a d e s o p e ra tio n s o f S y s te m 1 , lik e th o s e o f S y s te m 2 , a re n o t re s tric te d to th e p ro c e s s in g o f c u rre n t s tim u la tio n . In tu itiv e ju d g m e n ts d e a l w ith c o n c e p ts a s w e ll a s w ith p e rc e p ts a n d Process & Content in Two cognitive Systems F ig u r e 1 P r o c e s s a n d C o n te n t i n T w o C o g n i ti v e S y s te m s 698
From D. Kahneman: A perspective on judgment and choice, 2003, American Psychologist. S e p te m b e r 2 0 0 3 A m e ric a n P s y c h o lo g is t System 1 and System 2 The Elephant and the Rider (Haidt) The elephant - System 1 (Barghs Wise Unconscious)
Makes most day to day decisions The rider - System 2 Has some input, but not as much as we think Acts as an Interpreter Module (Gazzaniga) Fabricates reasons for behavior Makes errors in guessing those reasons Wanting vs. Liking Liking depends more on System 1 and automaticity
Wanting depends more on System 2 Influenced by socialization, gender proscriptions, ... Subject to heuristics and errors Wanting vs. Liking What do I want? is really: What would somebody like me want? What would/should somebody with my identity/self concept want?
But identity is a socially constructed entity My story is ABOUT reality, not reality itself The heart has its reasons, that reason knows not of. Pascal Theres someone in my head, but its not me. Pink Floyd
Were Lawyers, Not Scientists We hold the belief we want to believe Then recruit anything we can to support it. Peter Ditto, UC Irvine Mark Twain: It aint what you dont know that gets you into trouble. Its what you know for sure that aint so that gets you into trouble.
Wanting Liking Implications for career counseling A particular issue for the matching model Matching Model Self-knowledge What do you want in your work? World of work knowledge What's out there?
True reasoning (Frank Parsons) Match the first to the second Match me to work that will bring me happiness Matching Model What I really need to match to: Is not what I WANT But what I'd LIKE Matching Model
A better question: What kind of work will give me what I Like? Figure out what you Like-& Plan with that knowledge BUTWanting is cheap Liking is expensive Wanting is cheap data I can just make up what I want Liking is expensive data I have to develop a history of liking
across domains and time Knowing my Likes Thomas Motl: Teasing out wanting & liking Beforehand: Do you think you will like it? While you are doing it: Do you like it? Tomorrow: Did you like it? Ask me on an interest inventory: "Is this something you like?" Knowing my Likes
System 1: You have to put yourself in places where you have the opportunity To Like or To Not Like System 2: You have to pay attention to what happens AND you have to know that System 2 is subject to errors and distortions Trilateral Model of Adaptive CDM Reason
System 2, Rational System, Reflective System. Intuition System 1, Experiential System, Reflexive System. Engagement Activities that increase ones fund of
information and experience. The Case for Engagement taking part in behaviors that contribute to the career decisionmakers fund of information and experience. Makes both Rational & Intuitive tools more informed and less naive The Case for Engagement
Naive Naive Rationality Naive Intuition Examples of Occupational Engagement
Studying abroad Being involved in organizations Talking to anyone at anytime about anything Volunteering Job shadowing Traveling Reading a section of the newspaper you normally dont
31 Anti-Engagement Messages Students Hear Choose a major by the time you have 45 credit hours You already have a good paying summer job, dont take an internship that pays less Study Abroad will only extend your time in college Your school work is your job,
So dont volunteer or get a part time job. Go take that test, it will tell you what to do. All you can do with a history degree is teach The most important thing is your grades 32 Our firmest conclusion: Be Engaged!!! Better chance your intuition will be expert Be prepared! (always be engaged)
Ebberweins study of laid off workers 33 Implications for Career Counseling Career Counseling clients need convincing about all of this Hard Sell Invest time and energy in learning your Likes Move out of your comfort zone
Recognize your mind is something of a parasite (in that YOU are not YOUR MIND) Implications for Career Counseling Integrate well-researched counseling interventions that address behavior change Implications for Career Counseling
Stages of change I need to do the work to learn my likes Where am I in that process? Implications for Career Counseling Motivational Interviewing I'm ambivalent about engaging in that hard work Implications for Career Counseling
Acceptance and Commitment Therapy My thoughts (System 2) are subject to all manner of social influence My thoughts are not reality My thoughts have an agenda of their own, often not the same as the agenda I have for my life Takeaway message Happiness research tells us: Knowing what you like is hard That makes matching more complicated
Career counselors can use behavior change tools to encourage engagement Things to do while youre waiting for luck 1. Being a great student and worker is not enough We need to be adaptive agents With a healthy relationship to the marketplace. 2. Avoid choosing until you have developed your expertise Differentiate Decidedness from Commitment 3. Dont always trust what your thoughts are telling you.
Your thoughts are not your friends. Rational explanations may be driven by other agendas Things to do while youre waiting for luck 4. Feed your intuition Engage your 11,000,000 bit processor Instead of your 20 bit processor 5. Consult with trusted others, especially on your strengths 6. Dont spend too much time in self assessment
Things to do while youre waiting for luck 7. Most of all, ENGAGE Set yourself up for planned happenstance 8. Once (re)employed, STAY engaged 9. Choose Action over Decision (Savickas) 10. Lead a value-driven life Instead of a quest for a pain-free life So Dude, like, get out in the world and have some
Da un colloquio tra Hunt e Rossetti Raymond Watkinson, Pre-Raphaelite Art and Design, 1970. "That choiche of colours, blue-green, purples, violet, (…) came to be one of the marks of much Preraphaelite painting; colour which, however naturalistically rendered, was selective,...
Can EMS predict significant TBI? So Who is an EPIC Patient? ... Documentation. Document . VS q 5 min (including GCS, SPO. 2, ETCO. 2) Total Fluids given. Fingerstick. Blood Glucose (Treat if low) Care given, even if not consistent...
AYAs report levels of physical activity comparable to controls, below recommended guidelines. High proportion of AYAs report being overweight (20%) or obese (15%) with higher rate of obesity among AYAs (31%) than controls (27%)
Ovid's Art of Love (Ars amatoria). Ideology, Poetry, Empire. Marine Venus - Pompeii, 1st cent. CE. Ovid. according to the Roman historian Tacitus, "the worst class of enemies are those who praise" (Barton, Agr.
Ryan Gory Alexandra Mendoza Carlos Parra Spencer Porter Corey Souders Interest Meeting September 21st at 6:30 B210/B211 Juan Amorosi Natalia Ariza Carlos Gasteazoro Martin John German Nelson Fitz German Industrial Engineering Tau Beta Pi The Engineering Honor Society Recognizes these...
The MIPS ISA. Used as the example throughout the book. Stanford MIPS commercialized by MIPS Technologies (www.mips.com) Large share of embedded core market. Applications in consumer electronics, network/storage equipment, cameras, printers, … Typical of many modern ISAs. See MIPS Reference...
Preserve America Community:Suffolk, Virginia S. uffolk's rich history dates back to 1608 when the English settled here and traded with the Nansemond Indians. Captain John Smith noted the potential of the oyster beds in the Nansemond River, but was driven...
Ready to download the document? Go ahead and hit continue!