Wrap up

Final exam date/time

May 2nd @ 3pm.

Final exam location

GBS 234.

Final exam cumulative?

NOT cumulative.

Final exam format overview

14 multiple choice + 2 short answer + 1 long-answer (case essay).

Multiple choice section details

14 multiple choice questions; same style as midterm; 42 points total.

Short answer section details

2 short answer; total 8 points; about 3–4 sentences each; same style as midterm.

Long answer section details

1 long-answer; 50 points; multi-paragraph essay based on a case with guiding questions.

Permitted notes

3 by 5 index card permitted.

AI definition (course framing)

AI goes beyond LLMs (ChatGPT/Claude/Gemini) and includes other NLP models, computer vision, and generative image models.

AI adoption trend at work

AI adoption at work has increased exponentially since ChatGPT.

AI implications prompt (management/OB)

Consider effects on task significance, competence/self-efficacy, and perceptions of organizational justice.

AI & OB (good): time savings

Consistent AI users say it helps cut down work time.

AI & OB (good): self-efficacy effect

AI can increase self-efficacy by filling gaps in understanding and outsourcing tedious work when overloaded.

AI & OB (good): meaningful work link

If used correctly, AI could make work feel more motivating and meaningful.

AI & OB (good): SDT connection

Self-determination theory: consider autonomy, competence, and relatedness in how AI changes motivation.

AI & OB (good): organizational outcomes

Organizations using AI in processes show better high-level outcomes (performance, revenue, innovation).

AI & OB (bad): bias amplification risk

AI (especially LLMs) is trained on human behavior—so it can reflect/amplify human biases.

AI & OB (bad): justice perceptions

Knowing AI/algorithms made a decision can decrease interactional and procedural justice perceptions.

Procedural justice concern with AI

If people feel the process is opaque/unfair, procedural justice perceptions drop.

Interactional justice concern with AI

If a “machine decision” feels disrespectful/unempathetic or blocks real dialogue, interactional justice can drop.

Accountability problem with AI errors

When AI makes a mistake, responsibility becomes unclear (“who is responsible?”).

Deskilling (definition)

Loss of competence/self-efficacy because we outsource thinking too much.

Mindless AI use consequence

Overuse can reduce competence and self-efficacy (“becoming mindless”).

AI doesn’t challenge you (risk)

AI is servile and doesn’t spontaneously challenge decisions—can weaken moral decision-making over time.

AI & relationships at work

Belief that AI is being used can make people less attentive or more dismissive.

AI and respect signal

“I think you used AI” can be interpreted as “you don’t respect my time.”

AI and anxiety

AI can increase anxiety.

Precarious work (definition)

Low job security, unequal income distribution, low access to healthcare, etc.

AI and precarious work perception

AI can increase perceptions of precarious work due to automation/replacement threat.

Responsible AI use advice

Engage with AI, but responsibly.

Leadership moderates AI outcomes

AI can lead to more engagement (not less) under a “good leader.”

Good AI use cases (examples)

Coding, iterating on ideas, planning, organizing.

Bad AI use case example (humor point)

Sending an email—maybe use the keyboard instead.

OB topics covered (course map)

Individual differences/personality; attitudes/behaviors; decision-making; motivation/goal-setting; affect; diversity; ethics; power/influence; leadership; negotiations; social networks; groups/teams; culture/change; wellbeing/stress; social movements.

Organizational Behavior (OB) definition

Systematic study and application of knowledge about how individuals and groups act within organizations.

OB draws from (disciplines)

Psychology, sociology, economics, political science.

Goals of OB (2)

Understand and predict human behavior using scientific evidence.

Why OB matters (big idea)

Organizations are made of people and are inherently social; employers care about OB topics.

To succeed in organizations, you must… (list)

Make decisions, be part of a team, motivate/influence others, manage diversity, drive change.

Course goals (3)

Increase OB knowledge; apply OB concepts; develop leadership/management potential.

Key takeaway: humans have biases

Biases are normal (decision-making, perception, attributions), so there’s room for growth.

Key takeaway: how to improve decisions

Be open-minded; seek evidence; don’t rely only on common sense; use multiple perspectives.

Key takeaway: behavior is predictable

Patterns can be anticipated; strong leaders manage biases, diversity, group dynamics, and change proactively.

Happiness slide: main warning

Money/fame/accomplishments/career success alone won’t reliably produce long-term happiness.

Happiness driver #1: relationships

Career shapes your relationships; quality matters more than quantity; money can’t replace people to share life with.

Happiness driver #2: experiences

Material goods don’t produce long-term happiness; passion + experiences matter; you’ll remember who/what you did more than course content.

Happiness driver #3: personal freedom

Stop caring what others think; don’t let others’ judgments decide your happiness; only you know what’s best—be your best version.

Course evaluations note

Evaluations are important and take