Summary: This module provides three frameworks that are essential to Computer and Engineering Ethics classes being taught at the University of Puerto Rico - Mayaguez during the academic year of 2006-7. The first framework converts the Software Development Cycle into a decision-making framwork consisting of problem specification, solution generation, solution testing, and solution implementation. The second framework zeros in on the solution testing phase of the software development cycle by offering four tests to evaluate and rank solutions in terms of their ethical implications. The third framework offers a feasibility test designed to identify obstacles to implementing solutions that arise from situational constraints like resource, interest, and technical limitations. These frameworks are abbreviated from materials that will eventually be published in Good Computing: A Virtue Approach to Computer Ethics that is being authored by Chuck Huff, William Frey, and Jose Cruz-Cruz. They can also be supplimented by consulting www.computingcases.org and Engineering Ethics: Concepts and Cases by Rabins, Harris, and Pritchard.
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In this module you will learn and practice three frameworks designed to integrate ethics into decision making in the areas of practical and occupational ethics. The first framework divides the decision making process into four stages: problem specification, solution generation, solution testing, and solution implementation. It is based on an analogy between ethics and design problems that is detailed in a table presented below. The second framework focuses on the process of solution testing by providing four tests that will help you to evaluate and rank alternative courses of action. The reversibility, harm/beneficence, and public identification tests each "encapsulate" or summarize an important ethical theory. A value realization test assesses courses of action in terms of their ability to realize or harmonize different moral and nonmoral values. Finally, a feasibility test will help you to uncover interest, resource, and technical constraints that will affect and possibly impede the realization of your solution or decision. Taken together, these three frameworks will help steer you toward designing and implementing ethical decisions the professional and occupational areas.
Two online resources provide more extensive background information. The first, www.computingcases.org, provides background information on the ethics tests, socio-technical analysis, and intermediate moral concepts. The second, http://onlineethics.org/essays/education/teaching.html, explores in more detail the analogy between ethics and design problems. Much of this information will be published in Good Computing: A Virtue Approach to Computer Ethics, a textbook of cases and decision making techniques in computer ethics that is being authored by Chuck Huff, William Frey, and Jose A. Cruz-Cruz.
Traditionally, decision making frameworks in professional and occupational ethics have been taken from rational decision procedures used in economics. While these are useful, they lead one to think that ethical decisions are already "out there" waiting to be discovered. In contrast, taking a design approach to ethical decision making emphasizes that ethical decisions must be created, not discovered. This, in turn, emphasizes the importance of moral imagination and moral creativity. Carolyn Whitbeck in Ethics in Engineering Practice and Research describes this aspect of ethical decision making through the analogy she draws between ethics and design problems in chapter one. Here she rejects the idea that ethical problems are multiple choice problems. We solve ethical problems not by choosing between ready made solutions given with the situation; rather we use our moral creativity and moral imagination to design these solutions. Chuck Huff builds on this by modifying the design method used in software engineering so that it can help structure the process of framing ethical situations and creating actions to bring these situations to a successful and ethical conclusion. The key points in the analogy between ethical and design problems are summarized in the table presented just below.
| Analogy between design and ethics problem-solving | |
| Design Problem | Ethical Problem |
| Construct a prototype that optimizes (or satisfices) designated specifications | Construct a solution that integrates and realizes ethical values (justice, responsibility, reasonableness, respect, and safety) |
| Resolve conflicts between different specifications by means of integration | Resolve conflicts between values (moral vs. moral or moral vs. non-moral) by integration |
| Test prototype over the different specifications | Test solution over different ethical considerations encapsulated in ethics tests |
| Implement tested design over background constraints | Implement ethically tested solution over resource, interest, and technical constraints |
(1) problem specification, (2) solution generation, (3) solution testing, and (4) solution implementation.
Problem specification involves exercising moral imagination to specify the socio-technical system (including the stakeholders) that will influence and will be influenced by the decision we are about to make. Stating the problem clearly and concisely is essential to design problems; getting the problem right helps structure and channel the process of design and implementing the solution. There is no algorithm available to crank out effective problem specification. Instead, we offer a series of guidelines or rules of thumb to get you started in a process that is accomplished by the skillful exercise of moral imagination.
| Problem Type | Sub-Type | Solution Outline | ||||||
| Disagreement |
|
|||||||
| Conflict |
|
Value Integrative | Partially Value Integrative | Trade Off | ||||
| Framing |
|
Strategy for maintaining integrity | Strategy for restoring justice | Value integrative, design strategy | ||||
| Intermediate Moral Value | Public Welfare, Faithful Agency, Professional Integrity, Peer Collegiality | Realizing Value | Removing value conflicts | Prioritizing values for trade offs | ||||
In solution generation, agents exercise moral creativity by brainstorming to come up with solution options designed to resolve the disagreements and value conflicts identified in the problem specification stage. Brainstorming is crucial to generating nonobvious solutions to difficult, intractable problems. This process must take place within a non-polarized environment where the members of the group respect and trust one another. (See the module on the Ethics of Group Work for more information on how groups can be successful and pitfalls that commonly trip up groups.) Groups effectively initiate the brainstorming process by suspending criticism and analysis. After the process is completed (say, by meeting a quota), then participants can refine the solutions generated by combining them, eliminating those that don't fit the problem, and ranking them in terms of their ethics and feasibility. If a problem can't be solved, perhaps it can be dissolved through reformulation. If an entire problem can't be solve, perhaps the problem can be broken down into parts some of which can be readily solved.
| Solution/Test | Reversibility | Harm/ Beneficence | Virtue | Value | Code |
| Descrip-tion | Is the solution reversible with stakeholders? Does it honor basic rights? | Does the solution produce the best benefit/harm ratio? Does the solution maximize utility? | Does the solution express and integrate key virtues? | Moral values realized? Moral values frustrated? Value conflicts resolved or exacerbated? | Does the solution violate any code provisions? |
| Best solution | |||||
| Second Best | |||||
| Worst |
D. Solution implementation:
The chosen solution must be examined in terms of how well it responds to various situational constraints that could impede its implementation. What will be its costs? Can it be implemented within necessary time constraints? Does it honor recognized technical limitations or does it require pushing these back through innovation and discovery? Does it comply with legal and regulatory requirements? Finally, could the surrounding organizational, political, and social environments give rise to obstacles to the implementation of the solution? In general this phase requires looking at interest, technical, and resource constraints or limitations. A Feasibility Matrix helps to guide this process.
| Feasibility Matrix | ||
| Resource Constraints | Technical Constraints | Interest Constraints |
| Personalities | ||
| Time | Organizational | |
| Cost | Applicable Technology | Legal |
| Materials | Manufacturability | Social, Political, Cultural |
II. Ethical Frameworks:
Three ethics tests (reversibility, harm/beneficence, and public identification) encapsulate three ethical approaches (deontology, utilitarianism, and virtue ethics) and form the basis of stage three of the SDC, solution testing. A fourth test (a value realization test) builds upon the public identification/virtue ethics test by evaluating a solution in terms of the values it harmonizes, promotes, protects, or realizes. Finally a code test provides an independent check on the ethics tests and also highlights intermediate moral concepts such as safety, health, welfare, faithful agency, conflict of interest, confidentiality, professional integrity, collegiality, privacy, property, free speech, and equity/access). The following section provides advice on how to use these tests. More information can be found at www.computingcases.org.
1. Set-Up (These preliminary procedures are required to set-up the analysis performed under each test.)
Set-Up Pitfalls: Mistakes in this area lead to the analysis becoming unfocused and getting lost in irrelevancies. (a) Agent-switching where the analysis falls prey to irrelevancies that crop up when the test application is not grounded in the standpoint of a single agent, (b) Sloppy action-description where the analysis fails because no specific action has been tested, (c) Test-switching where the analysis fails because one test is substituted for another. (For example, the public identification and reversibility tests are often reduced to the harm/beneficence test where harmful consequences are listed but not associated with the agent or stakeholders.)
5. Code of Ethics Test
a. Does the action hold paramount the health, safety, and welfare of the public, i.e., those affected by the action but not able to participate in its design or execution?
b. Does the action maintain faithful agency with the client by not abusing trust, avoiding conflicts of interest, and maintaining confidences?
c. Is the action consistent with the reputation, honor, dignity, and integrity of the profession?
d. Does the action serve to maintain collegial relations with professional peers?
Meta-Tests:
a. When the ethics tests converge on a given solution, this convergence is a sign of the strength and robustness of the solution and counts in its favor.
b. When a given solution responds well to one test but does poorly under another, this is a sign that the solution needs further development and revision. It is not a sign that one test is relevant while the others are not. Divergence between test results is a sign that the solution is weak.
IV. Solution Implementation
This stage requires carrying out a Feasibility Test which identifies constraints that could interfere with realizing a solution. This test also sorts out constraints into resource (time, cost, materials), interest (individuals, organizations, legal, social, political), and technical limitations. By identifying situational constraints, problem-solvers can anticipate implementation problems and take early steps to prevent or mitigate them.
a. Time. Is there a deadline within which the solution has to be enacted? Is this deadline fixed or negotiable?
b. Financial. Are there cost constraints on implementing the ethical solution? Can these be extended by raising more funds? Can they be extended by cutting existing costs? Can agents negotiate for more money for implementation?
c. Technical. Technical limits constrain the ability to implement solutions. What, then, are the technical limitations to realizing and implementing the solution? Could these be moved back by modifying the solution or by adopting new technologies?
d. Manufacturability. Are there manufacturing constraints on the solution at hand? Given time, cost, and technical feasibility, what are the manufacturing limits to implementing the solution? Once again, are these limits fixed or flexible, rigid or negotiable?
e. Legal. How does the proposed solution stand with respect to existing laws, legal structures, and regulations? Does it create disposal problems addressed in existing regulations? Does it respond to and minimize the possibility of adverse legal action? Are there legal constraints that go against the ethical values embodied in the solution? Again, are these legal constraints fixed or negotiable?
f. Individual Interest Constraints. Individuals with conflicting interests may oppose the implementation of the solution. For example, an insecure supervisor may oppose the solution because he fears it will undermine his authority. Are these individual interest constraints fixed or negotiable?
g. Organizational. Inconsistencies between the solution and the formal or informal rules of an organization may give rise to implementation obstacles. Implementing the solution may require support of those higher up in the management hierarchy. The solution may conflict with organization rules, management structures, traditions, or financial objectives. Once again, are these constraints fixed or flexible?
h. Social, Cultural, or Political. The socio-technical system within which the solution is to be implemented contains certain social structures, cultural traditions, and political ideologies. How do these stand with respect to the solution? For example, does a climate of suspicion of high technology threaten to create political opposition to the solution? What kinds of social, cultural, or political problems could arise? Are these fixed or can they be altered through negotiation, education, or persuasion?
The Feasibility Tests focuses on situational constraints. How could these hinder the implementation of the solution? Should the solution be modified to ease implementation? Can the constraints be removed or remodeled by negotiation, compromise, or education? Can implementation be facilitated by modifying both the solution and changing the constraints?