Decision Making Problem Solving Dona Warren Department of

Decision Making Problem Solving Dona Warren Department of Philosophy The University of Wisconsin – Stevens Point

Decision Making

What major should I choose?

Art? I know I’d enjoy studying that, but it might make my parents unhappy, and what if I can’t find a job? What major should I choose?

Art? I know I’d enjoy studying that, but it might make my parents unhappy, and what if I can’t find a job? What major should I choose? Computer science? I find that a bit dull, but I think that I could get a job with it. I might even be able to retire early.

Art? I know I’d enjoy studying that, but it might make my parents unhappy, and what if I can’t find a job? What major should I choose? Computer science? I find that a bit dull, but I think that I could get a job with it. I might even be able to retire early. Education? I’d enjoy that more than computer science, but my salary might be lower. I would be able to help children, however. That’s a plus.

Art? I know I’d enjoy studying that, but it might make my parents unhappy, and what if I can’t find a job? What major should I choose? Computer science? I find that a bit dull, but I think that I could get a job with it. I might even be able to retire early. Education? I’d enjoy that more than computer science, but my salary might be lower. I would be able to help children, however. That’s a plus. When deciding what to do, we need to consider:

1) What our Options are A (Majoring in Art) C (Majoring in Computer Science) E (Majoring in Education)

2) The Possible Consequences of Each Option (Enjoyment) A P (Unhappy Parents) (Unemployment) D C (Dull) (Job) (Early Retirement) (Some Enjoyment) E L (Lower Salary) (Helping Children)

2) The Possible Consequences of Each Option (Enjoyment) A P (Unhappy Parents) (Unemployment) D C (Dull) (Job) (Early Retirement) (Some Enjoyment) E L (Lower Salary) (Helping Children) Morally responsible decision making involves considering how our actions will affect us…

2) The Possible Consequences of Each Option (Enjoyment) A P (Unhappy Parents) (Unemployment) D C (Dull) (Job) (Early Retirement) (Some Enjoyment) E Morally responsible decision making involves considering how our actions could affect us… L (Lower Salary) (Helping Children) … and the world around us (other people and the non-human environment).

3) How Good or Bad Each Consequence Would Be. A E (Enjoyment – Very Good) P (Unhappy Parents – Somewhat Bad) (Unemployment – Very Bad) D C (Dull – Somewhat Bad) (Job – Somewhat Good) (Early Retirement – Very Good) (Some Enjoyment – Somewhat Good) E L (Lower Salary – Somewhat Bad) (Helping Children – Very Good)

4) How Likely Each Consequence is. Certain Impossible E A P D C E L

4) How Likely Each Consequence is. Certain Impossible E Note: D Intensely good or bad consequences naturally capture our attention and have a certain psychological salience. A C E It does not follow from this, however, that they are more likely to occur than less emotionally charged consequences. L Intensity and probability are unrelated.

Yes, that’s all well and good. But I still don’t know what to do.

Yes, that’s all well and good. But I still don’t know what to do. How can I compare a mildly bad but highly probable consequence to a consequence that’s very good but less likely?

Yes, that’s all well and good. But I still don’t know what to do. How can I compare a mildly bad but highly probable consequence to a consequence that’s very good but less likely? Math can help us out.

Yes, that’s all well and good. But I still don’t know what to do. How can I compare a mildly bad but highly probable consequence to a consequence that’s very good but less likely? Math can help us out. Delightful! I enjoy mathematics.

When deciding whether or not to play a game of chance, we need to consider: ü how much we stand to lose ü the probability of losing ü how much we stand to win ü the probability of winning We need to compare a mildly bad but highly probable consequence (losing the game) to a consequence that’s very good but less likely (winning the game).

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games.

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games. Since you have PW% chance of winning , and since you played 100 games, we can assume that you won PW times. Each time you won, you netted amount W. So, in all, you netted PW*W from your winning games.

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games. Since you have PW% chance of winning , and since you played 100 games, we can assume that you won PW times. Each time you won, you netted amount W. So, in all, you netted PW*W from your winning games. Since you have PL% chance of losing, and since you played 100 games, we can assume that you lost PL times. Each time you lost, you forfeited amount L. So, in all, you forfeited PL*L from your losing games.

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games. Since you have PW% chance of winning , and since you played 100 games, we can assume that you won PW times. Each time you won, you netted amount W. So, in all, you netted PW*W from your winning games. Since you have PL% chance of losing, and since you played 100 games, we can assume that you lost PL times. Each time you lost, you forfeited amount L. So, in all, you forfeited PL*L from your losing games. Your total winnings or losing, after you play 100 games, is your net winnings minus your net losses: PW*W – PL*L

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games. Since you have PW% chance of winning , and since you played 100 games, we can assume that you won PW times. Each time you won, you netted amount W. So, in all, you netted PW*W from your winning games. Since you have PL% chance of losing, and since you played 100 games, we can assume that you lost PL times. Each time you lost, you forfeited amount L. So, in all, you forfeited PL*L from your losing games. Your total winnings or losing, after you play 100 games, is your net winnings minus your net losses: PW*W – PL*L If we wanted to see how much you won or lost, on average, per game, we’d divide your total winnings or losings by the number of games you played: (PW*W - PL*L)/100. Now for a bit of math: (PW*W - PL*L)/100 = (PW*W) /100 - (PL*L)/100 = (PW/100)*W - (PL/100)*L = PW%*W - PL%*L = W*PW% - L*PL%

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games. Since you have PW% chance of winning , and since you played 100 games, we can assume that you won PW times. Each time you won, you netted amount W. So, in all, you netted PW*W from your winning games. Since you have PL% chance of losing, and since you played 100 games, we can assume that you lost PL times. Each time you lost, you forfeited amount L. So, in all, you forfeited PL*L from your losing games. Your total winnings or losing, after you play 100 games, is your net winnings minus your net losses: PW*W – PL*L If we wanted to see how much you won or lost, on average, per game, we’d divide your total winnings or losings by the number of games you played: (PW*W - PL*L)/100. Now for a bit of math: (PW*W - PL*L)/100 = (PW*W) /100 - (PL*L)/100 = (PW/100)*W - (PL/100)*L = PW%*W - PL%*L = W*PW% - L*PL% This is called your expected utility. If you play this game, you can expect to win or lose, on average, W*PW% - L*PL%

“W” is how much you’ll net, if you win. “L” is how much you’ll forfeit, if you lose. “PW%” is your probability of winning. “PL%” is your probability of losing. Suppose you play 100 games. Since you have PW% chance of winning , and since you played 100 games, we can assume that you won PW times. Each time you won, you netted amount W. So, in all, you netted PW*W from your winning games. Since you have PL% chance of losing, and since you played 100 games, we can assume that you lost PL times. Each time you lost, you forfeited amount L. So, in all, you forfeited PL*L from your losing games. Your total winnings or losing, after you play 100 games, is your net winnings minus your net losses: PW*W – PL*L Assuming that gambling doesn’t If we wanted to see how much you won or lost, on violate your moral code: average, per game, we’d divide your total winnings • If the expected utility is positive then or losings by the number of games you played: you can expect to earn money in the (PW*W - PL*L)/100. long run and you should play the Now for a bit of math: (PW*W - PL*L)/100 = game. (PW*W) /100 - (PL*L)/100 = • If the expected utility is negative (PW/100)*W - (PL/100)*L = then you can expect to lose money PW%*W - PL%*L in the long run and you shouldn’t W*PW% - L*PL% play. • If you’re faced with multiple games This is called your expected utility. then you should play the one with If you play this game, you can expect the highest expected utility. to win or lose, on average, W*PW% - L*PL%

The rationality of betting is a function of: 1. How much we stand to win. 2. How much we stand to lose. 3. Our chances of winning and losing.

The rationality of betting is a function of: 1. How much we stand to win. 2. How much we stand to lose. 3. Our chances of winning and losing. A raffle ticket costs $10. The prize is $50. The chance of winning is 25%. If we win, we’d net $40. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (40)(25%)-(10)(75%) =10 – 7. 5 = 2. 5.

The rationality of betting is a function of: A raffle ticket costs $10. The prize is $50. The chance of winning is 25%. If we win, we’d net $40. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (40)(25%)-(10)(75%) =10 – 7. 5 = 2. 5. A raffle ticket costs $10. The prize is $30. The chance of winning is 25%. 1. How much we stand to win. 2. How much we stand to lose. 3. Our chances of winning and losing. If we win, we’d net $20. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (20)(25%)-(10)(75%) = 5 – 7. 5 = -2. 5.

The rationality of betting is a function of: A raffle ticket costs $10. The prize is $50. The chance of winning is 25%. If we win, we’d net $40. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (40)(25%)-(10)(75%) =10 – 7. 5 = 2. 5. A raffle ticket costs $10. The prize is $30. The chance of winning is 25%. 1. How much we stand to win. 2. How much we stand to lose. 3. Our chances of winning and losing. If we win, we’d net $20. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (20)(25%)-(10)(75%) = 5 – 7. 5 = -2. 5. A raffle ticket costs $4. The prize is $30. The chance of winning is 25%. If we win, we’d net $26. Our chance of winning is 25%. If we lose, we’d lose $4. Our chance of losing is 75%. Our expected utility, then, is (26)(25%)-(4)(75%) = 6. 5 – 3 = 3. 5.

The rationality of betting is a function of: A raffle ticket costs $10. The prize is $50. The chance of winning is 25%. If we win, we’d net $40. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (40)(25%)-(10)(75%) =10 – 7. 5 = 2. 5. A raffle ticket costs $10. The prize is $30. The chance of winning is 25%. 1. How much we stand to win. 2. How much we stand to lose. 3. Our chances of winning and losing. If we win, we’d net $20. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (20)(25%)-(10)(75%) = 5 – 7. 5 = -2. 5. A raffle ticket costs $4. The prize is $30. The chance of winning is 25%. If we win, we’d net $26. Our chance of winning is 25%. If we lose, we’d lose $4. Our chance of losing is 75%. Our expected utility, then, is (26)(25%)-(4)(75%) = 6. 5 – 3 = 3. 5. A raffle ticket costs $4. The prize is $30. The chance of winning is 12. 5%. If we win, we’d net $26. Our chance of winning is 12. 5%. If we lose, we’d lose $4. Our chance of losing is 87. 5%. Our expected utility, then, is (26)(12. 5%)-(4)(87. 5%) = 3. 25 – 3. 5 = -0. 25.

The rationality of betting is a function of: A raffle ticket costs $10. The prize is $50. The chance of winning is 25%. If we win, we’d net $40. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (40)(25%)-(10)(75%) =10 – 7. 5 = 2. 5. A raffle ticket costs $10. The prize is $30. The chance of winning is 25%. 1. How much we stand to win. 2. How much we stand to lose. 3. Our chances of winning and losing. If we win, we’d net $20. Our chance of winning is 25%. If we lose, we’d lose $10. Our chance of losing is 75%. Our expected utility, then, is (20)(25%)-(10)(75%) = 5 – 7. 5 = -2. 5. A raffle ticket costs $4. The prize is $30. The chance of winning is 25%. If we win, we’d net $26. Our chance of winning is 25%. If we lose, we’d lose $4. Our chance of losing is 75%. Our expected utility, then, is (26)(25%)-(4)(75%) = 6. 5 – 3 = 3. 5. A raffle ticket costs $4. The prize is $30. The chance of winning is 12. 5%. If we win, we’d net $26. Our chance of winning is 12. 5%. If we lose, we’d lose $4. Our chance of losing is 87. 5%. Our expected utility, then, is (26)(12. 5%)-(4)(87. 5%) = 3. 25 – 3. 5 = -0. 25. We should play the game that has the highest expected utility.

That’s all very interesting, but how does it help me?

We’ll calculate the “expected utility” of each of your possible majors by identifying the possible consequences of each decision, assigning numbers to indicate how good or bad each consequence would be, and estimating the probability of each consequence. For each consequence, we’ll multiply its “goodness or badness” by its probability. We’ll then add these numbers up, and that will give us the expected utility of that major. The “right” major is the major with the highest expected utility. That’s all very interesting, but how does it help me?

We’ll calculate the “expected utility” of each of your possible majors by identifying the possible consequences of each decision, assigning numbers to indicate how good or bad each consequence would be, and estimating the probability of each consequence. For each consequence, we’ll multiply its “goodness or badness” by its probability. We’ll then add these numbers up, and that will give us the expected utility of that major. The “right” major is the major with the highest expected utility. That’s all very interesting, but how does it help me? But isn’t assigning numbers to indicate how good or bad a certain consequence would be, and estimating the probability of each consequence, very subjective and artificial?

We’ll calculate the “expected utility” of each of your possible majors by identifying the possible consequences of each decision, assigning numbers to indicate how good or bad each consequence would be, and estimating the probability of each consequence. For each consequence, we’ll multiply its “goodness or badness” by its probability. We’ll then add these numbers up, and that will give us the expected utility of that major. The “right” major is the major with the highest expected utility. That’s all very interesting, but how does it help me? But isn’t assigning numbers to indicate how good or bad a certain consequence would be, and estimating the probability of each consequence, very subjective and artificial? This mathematical calculation is a just a guide. It’s a way of considering both the nature and the probability of the consequences of our options, and allowing the more probable consequences to carry more weight. Even if we don’t assign numbers and carry out the calculation, we should still do that.

Art How good or bad Probability Enjoy it +70 90% +63 Parents unhappy -30 60% -18 Not find a job -70 50% -35 10 Computer Science How good or bad Probability Find it dull -30 90% -27 Find a job +50 80% +40 Retire early +80 30% +24 37 Education How good or bad Probability Enjoy it +50 90% +45 Lower salary -10 90% -9 Help children +70 80% +56 92

So, according to this way of thinking, education is the best choice for me. But can’t this way of thinking go wrong? Mightn’t I realize in a few years that education was the wrong decision? Decision making is vulnerable to error. Some of these errors aren’t avoidable, but others are. By minimizing our avoidable errors, we can increase the chances that we’ll make the right decisions.

Element of Decision-Making Identifying our options. Think creatively. Talk to other people. Unavoidable Error Avoidable Error We can’t be expected to think of But we shouldn’t unduly narrow each and every option. our options.

Element of Decision-Making Identifying our options. Unavoidable Error Avoidable Error We can’t be expected to think of But we shouldn’t unduly narrow each and every option. our options. Identifying the consequences of We can’t predict all of the each option. consequences of our options. But we shouldn’t ignore reasonably predictable consequences. Consider how our actions might affect us and the world around us. Reflect upon our own past experiences. Avail ourselves of other people’s experience and research. Recognize and counter our optimistic / pessimistic biases.

Element of Decision-Making Identifying our options. Unavoidable Error Avoidable Error We can’t be expected to think of But we shouldn’t unduly narrow each and every option. our options. Identifying the consequences of We can’t predict all of the each option. consequences of our options. But we shouldn’t ignore reasonably predictable consequences. Estimating how good or bad each consequence would be. But we shouldn’t allow ourselves to be irrationally optimistic or pessimistic. Sometimes a consequence might be better, or worse, than we expect. Reflect upon our own past experiences. Avail ourselves of other people’s experience and research. Recognize and counter our optimistic / pessimistic biases.

Element of Decision-Making Identifying our options. Unavoidable Error Avoidable Error We can’t be expected to think of But we shouldn’t unduly narrow each and every option. our options. Identifying the consequences of We can’t predict all of the each option. consequences of our options. But we shouldn’t ignore reasonably predictable consequences. Estimating how good or bad each consequence would be. Sometimes a consequence might be better, or worse, than we expect. But we shouldn’t allow ourselves to be irrationally optimistic or pessimistic. Estimating how likely each consequence is. Sometimes we might be legitimately mistaken about how likely a given consequence is. But we shouldn’t ignore good evidence indicating the probability of each consequence. Reflect upon our own past experiences. Avail ourselves of other people’s experience and research. Recognize and counter our optimistic / pessimistic biases. Don’t equate intensity with probability. Don’t equate proximity with probability.

1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall. Decision Making - Think creatively. - Talk to other people. - Consider how our actions might affect us and the world around us. - Reflect upon our own past experiences. - Avail ourselves of other people’s experience and research. - Recognize and counter our optimistic / pessimistic biases. - Don’t equate intensity with probability. - Don’t equate proximity with probability. When in doubt, utilize an expected utility formula: C 1 *PC 1% + C 2 *PC 2% + C 3 *PC 3% + … + Cn *PCn% Where “C” is a numerical representation of how good or bad a consequence would be and “PC%” is how likely it is that this consequence will occur.

1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall. Decision Making - Think creatively. - Talk to other people. - Consider how our actions might affect us and the world around us. - Reflect upon our own past experiences. - Avail ourselves of other people’s experience and research. - Recognize and counter our optimistic / pessimistic biases. - Don’t equate intensity with probability. - Don’t equate proximity with probability. Should I brush my teeth this evening? When in doubt, utilize an expected utility formula: C 1 *PC 1% + C 2 *PC 2% + C 3 *PC 3% + … + Cn *PCn% Where “C” is a numerical representation of how good or bad a consequence would be and “PC%” is how likely it is that this consequence will occur.

1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall. - Think creatively. - Talk to other people. - Consider how our actions might affect us and the world around us. - Reflect upon our own past experiences. - Avail ourselves of other people’s experience and research. - Recognize and counter our optimistic / pessimistic biases. - Don’t equate intensity with probability. - Don’t equate proximity with probability. Should I brush my teeth this evening? When in doubt, utilize an expected utility formula: C 1 *PC 1% + C 2 *PC 2% + C 3 *PC 3% + … + Cn *PCn% Where “C” is a numerical representation of how good or bad a consequence would be and “PC%” is how likely it is that this consequence will occur. Caveats: Use only for important decisions that we don’t need to make every day. Entrust other decisions to wisely cultivated habit. (We can use this method to help us decide what habits we want to cultivate. ) Decision Making

1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall. - Think creatively. - Talk to other people. - Consider how our actions might affect us and the world around us. - Reflect upon our own past experiences. - Avail ourselves of other people’s experience and research. - Recognize and counter our optimistic / pessimistic biases. - Don’t equate intensity with probability. - Don’t equate proximity with probability. Should I strangle my annoying neighbor in When in doubt, utilize an expected utility formula: his% + C sleep? C *PC % + … + C *PC % 1 1 2 2 3 3 n n Where “C” is a numerical representation of how good or bad a consequence would be and “PC%” is how likely it is that this consequence will occur. Caveats: Use only for important decisions that we don’t need to make every day. Entrust other decisions to wisely cultivated habit. (We can use this method to help us decide what habits we want to cultivate. ) Decision Making

1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall. - Think creatively. - Talk to other people. - Consider how our actions might affect us and the world around us. - Reflect upon our own past experiences. - Avail ourselves of other people’s experience and research. - Recognize and counter our optimistic / pessimistic biases. - Don’t equate intensity with probability. - Don’t equate proximity with probability. Should I strangle my annoying neighbor in When in doubt, utilize an expected utility formula: his% + C sleep? C *PC % + … + C *PC % 1 1 2 2 3 3 n n Where “C” is a numerical representation of how good or bad a consequence would be and “PC%” is how likely it is that this consequence will occur. Caveats: Use only for important decisions that we don’t need to make every day. Entrust other decisions to wisely cultivated habit. (We can use this method to help us decide what habits we want to cultivate. ) Decision Making Use only for decisions that are appropriately made on the basis of probable consequences.

1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall. - Think creatively. - Talk to other people. - Consider how our actions might affect us and the world around us. - Reflect upon our own past experiences. - Avail ourselves of other people’s experience and research. - Recognize and counter our optimistic / pessimistic biases. - Don’t equate intensity with probability. - Don’t equate proximity with probability. When in doubt, utilize an expected utility formula: C 1 *PC 1% + C 2 *PC 2% + C 3 *PC 3% + … + Cn *PCn% Where “C” is a numerical representation of how good or bad a consequence would be and “PC%” is how likely it is that this consequence will occur. Caveats: Use only for important decisions that we don’t need to make every day. Entrust other decisions to wisely cultivated habit. (We can use this method to help us decide what habits we want to cultivate. ) Decision Making Use only for decisions that are appropriately made on the basis of probable consequences.

Problem Solving

I’m feeling unfulfilled in my current job. Problem

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem It’s often more useful to think about the end that we want to achieve than it is to think about the problem.

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem I could ask for more challenging assignments in my current position. Means

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem I could ask for more challenging assignments in my current position. Means I could find another job. Means

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem I could ask for more challenging assignments in my current position. Means I could find another job. Means Or, I could just continue this way and decide to live without the job satisfaction I want. Abandoning the End

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem I could ask for more challenging assignments in my current position. Means I could find another job. Means Or, I could just continue this way and decide to live without the job satisfaction I want. Abandoning the End Options

I want greater job satisfaction. End I’m feeling unfulfilled in my current job. Problem I could ask for more challenging assignments in my current position. Means I could find another job. Means Or, I could just continue this way and decide to live without the job satisfaction I want. Abandoning the End Options Making Good Decisions: 1) Consider our options. 2) Identify the possible consequences of each option. 3) Estimate how good or bad each consequence would be. 4) Estimate the probability of each consequence. 5) Evaluate each option in light of the nature and probability of its consequences. 6) Select that option that’s best overall.

More Challenging Assignments How good or bad Probability Greater Job Satisfaction Alienate co-workers Get a promotion New Job Greater Job Satisfaction Lesser Job Satisfaction Reduction of Pay Live without Job Satisfaction Not Greater Job Satisfaction Seek Satisfaction Elsewhere

More Challenging Assignments How good or bad Probability Greater Job Satisfaction Alienate co-workers Get a promotion New Job Options that are means to the end will always have the attainment of the end as a consequence. How good or bad Probability Greater Job Satisfaction Lesser Job Satisfaction Reduction of Pay Live without Job Satisfaction Not Greater Job Satisfaction Seek Satisfaction Elsewhere The option that is the abandonment of the end will always have the non-attainment of the end as a consequence.

More Challenging Assignments How good or bad Probability Greater Job Satisfaction +90 75% +67. 5 Alienate co-workers -60 50% -30 Get a promotion +70 10% +7 +44. 5 New Job How good or bad Probability Greater Job Satisfaction Lesser Job Satisfaction Reduction of Pay Live without Job Satisfaction Not Greater Job Satisfaction Seek Satisfaction Elsewhere

More Challenging Assignments How good or bad Probability Greater Job Satisfaction +90 75% +67. 5 Alienate co-workers -60 50% -30 Get a promotion +70 10% +7 +44. 5 New Job How good or bad Probability Greater Job Satisfaction +90 60% +54 Lesser Job Satisfaction -90 30% -27 Reduction of Pay -60 10% -6 +21 Live without Job Satisfaction Not Greater Job Satisfaction Seek Satisfaction Elsewhere How good or bad Probability

More Challenging Assignments How good or bad Probability Greater Job Satisfaction +90 75% +67. 5 Alienate co-workers -60 50% -30 Get a promotion +70 10% +7 +44. 5 New Job How good or bad Probability Greater Job Satisfaction +90 60% +54 Lesser Job Satisfaction -90 30% -27 Reduction of Pay -60 10% -6 +21 Live without Job Satisfaction How good or bad Probability Not Greater Job Satisfaction -90 100% -90 Seek Satisfaction Elsewhere +40 100% +40 -50

Frankly, I’m disappointed that you even considered living without greater job satisfaction.

That’s defeatist thinking! You’ve got to fight for what you want! Frankly, I’m disappointed that you even considered living without greater job satisfaction.

That’s defeatist thinking! You’ve got to fight for what you want! Frankly, I’m disappointed that you even considered living without greater job satisfaction. It’s always better to solve a problem than to live with it!

That’s defeatist thinking! You’ve got to fight for what you want! It’s always better to solve a problem than to live with it! Frankly, I’m disappointed that you even considered living without greater job satisfaction. That’s nonsense.

“Pray, have you found a cure for my slightly malformed, but neither particularly painful nor incapacitating, left pinky toe? ” “Verily, my lord. We could cut it off. ”

“Pray, have you found a cure for my slightly malformed, but neither particularly painful nor incapacitating, left pinky toe? ” “Verily, my lord. We could cut it off. ” The Cure Worse than the Disease Fallacy: Any solution is better than no solution at all. In fact, sometimes the all of the possible solutions to a problem are worse than the problem itself, in which case it’s best to let the problem be (at least until a better solution presents itself).

1) Decide upon the end that we want to achieve. (It’s generally more helpful to focus on the end that we want to achieve than it is to focus on the problem. ) Problem Solving 2) Consider a variety of means to achieve that end. 3) Our options are all of those means plus the decision to not achieve the end. (Considering the option of not achieving the end allows us to avoid the Cure Worse than the Disease fallacy. ) 4) Identify the possible consequences of each option. (Options that are means to the end will include achieving the end as a consequence. The option that is deciding to not achieve the end will have not achieving the end as a consequence. ) 5) Estimate how good or bad each consequence would be. 6) Estimate the probability of each consequence. 7) Evaluate each option in light of the nature and probability of its consequences. 8) Select the option that’s best overall.

Decision Making Problem Solving