SOSC Science Technology and Society Today: Lesson 18 Ethics, Engineering and Business Novem ber 2, 1998 Dr. Vincent Duffy - IEEM ieem.ust.hk/dfaculty/duffy/

Disclosure of proprietary info n Yau works for ? u MPC now, Wai Nang previously u MPC allowed production by Chit Choi (H.K) u Did Yau know? When? n Who sues who? Why? u Wai Nang sues Chi Choi over patent (intellectual property) u MPC (Canada) gave production rights to Chi Choi u Yau in trouble if he knew MPC works with Chit Choi (within 2 years). Did he? 2

What if Yau used Total Benefit Test? n Why would Yau use total benefit test instead of Ethics-Plus or Rational technique? u no dilemma. more chance to quantify possibilities. u alternatives could have been evaluated before difficult situation came about n Total Benefit = sum (dim.wt.*benefit) u compare Total benefit for each alternative u ex. Yau -some decision dimensions u examples of weights (of dimension decisions) F use knowledge, get back at company, deception, become wealthy, risk of getting caught 3

u suppose: 1 -sell to MPC in Canada F w/out knowledge of connection to H.K.company F how to calculate using reading? F how do you measure benefit? from feeling good? dollars? improved or loss of reputation? F some things impact positively, some negatively F You would have to make these judgements (assumptions) as you decide u suppose: 2 - sell to MPC knowing they work with Chit Choi F worry about getting caught should be greater (w>0) What if Yau used Total Benefit Test? 4

Example 1 Suppose: no knowledge of MPC connection with Hong Kong company Alternative 1 ( j=1) : sell to MPC T j =  w i b ij = T 1 i = decision dimension j = decision alternative, probably best to sum weights to 1 ex. suppose benefit b comes from $ earned and dimensions (assume values for w and b): i=1 : wants to use knowledge, w 1 =.3, b 11 =$5k i=2 : wants to make money w 2 =.7, b 21 = $2M T j =  w i b ij = T 1 =.3(5k)+.7(2M)>1.4M Alternative 2 ( j=2): find work in another field T j =  w i b ij = T 2 dimensions: i=1 : wants to use knowledge, w 1 =.3, b 11 = $0 i=2 : wants to make money w 2 =.7, b 21 = $180k (15k/mo-3yrs) T j =  w i b ij = T 2 =.3(0)+.7(180k)(3)<.4M 5

Example 2 Suppose: no knowledge of MPC connection with Hong Kong company Alternative 1 ( j=1) : sell to MPC T j =  w i b ij = T 1 i = decision dimension j = decision alternative, probably best to sum weights to 1 ex. suppose benefit b comes from good feeling about work environment and dimension (assume values for w and b): i=1 : wants to use knowledge, w 1 =.2, b 11 = 30 (satisfaction units) i=2 : get back at former employer w 2 =.2, b 21 = 30 i=3 : worry about getting caught w 3 =0, b 31 = 30 i=4 : wants to make money w 4 =.6, b 41 = 30 T j =  w i b ij = T 1 =( )(30)=30 (satisfaction units) Alternative 2 ( j=2): find work in another field T j =  w i b ij = T 2 dimension: i=1 : wants to use knowledge, w 1 =.2 b 11 = 0 i=2 : get back at former employer w 2 =.2 b 21 = 0 i=3 : worry about getting caught w 3 =0 b 31 = 0 i=4 : wants to make money w 4 =.6 b 41 = 20 T j =  w i b ij = T 2 =.2(0)+.2(0)+0(0)+.6(20)= 12 (satisfaction units) 6

Example 3 A conservative look Suppose: knowledge of MPC connection with Hong Kong company Alternative 1 ( j=1) : sell to MPC T j =  w i b ij =.1(5k)+(.4-.3)(2M)=201k i = decision dimension j = decision alternative, probably best to sum weights to 1 ex. suppose benefit b comes from $ earned and dimensions (assume values for w and b): i=1 : wants to use knowledge, w 1 =.2, b 11 =$5k i=2 : get back at former employer w 2 =.1, b 21 = $0 i=3 : wants to make money w 3 =.4, b 31 = $2M i=4 : penalty for getting caught w 4 =.3, b 41 = $2M T j =  w i b ij =.2(5k)+(.4-.3)(2M)=201k Alternative 2 ( j=2): find work in another field dimensions: i=1 : wants to use knowledge, w 1 =.2, b 11 = $0 i=2 : get back at former employer w 2 =.1, b 21 = $0 i=3 : wants to make money w 3 =.4, b 31 =$180k $15k/mo (3yrs) i=4 : penalty for getting caught w 4 =.3, b 41 = $0 T j =  w i b ij =.2(0)+.4(180k)(3)+.4(0)= $216k 7

Suppose: knowledge of MPC connection with Hong Kong company (less conservative approach) Alternative 1 ( j=1) : sell to MPC T j =  w i b ij =.1(5k)+(.4-.3)(2M)=601k i = decision dimension j = decision alternative, probably best to sum weights to 1 ex. suppose benefit b comes from $ earned and dimensions (i=1-4) (assume values for w and b): i=1 : wants to use knowledge,w 1 =.2, b 11 =$5k i=2 : get back at former employer w 2 =.1, b 21 = $0 i=3 : wants to make money w 3 =.5, b 31 = $2M i=4 : penalty for getting caught w 4 =.2, b 41 = $2M T j =  w i b ij = T 1 =.2(5k)+.1(0)+ (.5-.2)(2M)=601k Alternative 2 ( j=2): find work in another field dimensions: i=1 : wants to use knowledge, w 1 =.2, b 11 = $0 i=2 : get back at former employer w 2 =.1, b 21 = $0 i=3 : wants to make money w 3 =.5, b 31 =$15k/mo $180k(3yrs) i=4 : penalty for getting caught w 4 =.2, b 41 = $0 T j =  w i b ij = ( )(0)+.5(180k)(3)= $216k 8

In summary: n Yau? alternatives could have been thought through beforehand F note the weights and benefits are estimated F decision dimensions are based on analysis of situation u example 1 F suppose no knowledge of MPC work w/H.K. F uses $ as the benefit measure F alternative 1 -work w/MPC better (>1.4M, compared to 1.4M, compared to <.4M) u example 2 F suppose no knowledge of MPC work w/H.K. F uses ‘feel good about work environment’ as benefit measure F alternative 1 - work w/MPC better (30 compared to 12 units) 9

In summary (cont.): u example 3 F suppose knowledge of MPC work w/H.K F conservative approach F close weighting between ‘get caught’ & ‘make money’ F benefit greater for work in another field ($216k vs. $201k) u example 4 F suppose knowledge of MPC work w/H.K F less conservative approach F weighting ‘get caught’ lower (less concern) F benefit greater for work w/MPC ($601k vs. $216k) 10

QOTD #1 n Q.1. What are two differences between Total Benefit Test and the other models we have looked at (ETHICS-Plus & Rational Technique)? u can quantify the decision making process u Total Benefit Test does not give guidelines for determining the important criteria for decision 11

QOTD#2 n Q.2. For Yau, in calculating the Total Benefit Test, how would he show a more conservative/less conservative approach? u less conservative approach F lower weight to ‘get caught’ shows less concern about risk u more conservative approach F closer/similar weight between ‘get caught’ and ‘make money’ 12

QOTD#3 n Q.3. What are two examples of decision dimensions, benefits? u 2 decision dimensions for Yau are F shown in example 1 F ‘wants to use knowledge’ F ‘wants to make money’ u 2 additional decision dimensions are F shown in example 2, 3 & 4 F ‘wants to get back at former employer Wai Nang’ F ‘worries about getting caught’ 13

QOTD#4 n Q.4. What should any Ethics Model allow you to do? u An ethics model may or may not allow for quantifying or determining the decision criteria. u All of the models shown have advantages and disadvantages. u However, any model used F should allow for a systematic way of approaching an ethical dilemma F this is the common theme for the 3 models presented (ETHICS-Plus, Rational Technique, Total Benefit Test 14

Administrative items n Wednesday u Homework 2 distributed F needs to include material from lecture Wednesday u utilizing concepts from: F politics of technology, innovations, ethics, law u delayed due date for homework F due Wednesday 11 (not Monday 9th) F oral presentations in class on Wednesday 11th.