Question

Please answer the question based on your knowledge of your operation managements. No textbook required for this question and just one paragraph each

2. Explain the differences between outcomes, causes, and risks. Provide and example of each. What are the implications of confusing these?

3. Is the term inherent risk helpful? How could it help and/or hinder the assessment of risk?

4. What are the possible complications of moving from assessments of predefined sets of risks to using top-down objectives based on the balanced score card approach?

5. How does voting technology work? Discuss the advantages and disadvantages of using voting technology compared with other approaches such as those described in this case study.

Answer 1

It is natural for us to ponder the relationship between cause and effect. If one can identify causes, then it is possible to predict future events to some extent. The notion of causation also provides a basis for praise and credit if the effect was desirable or blame if was not.

We all have an intuitive idea of what we think of as a "cause," but how does one define what a cause is? What are the criteria that need to be met in order to say that a factor (or exposure, determinant) is a cause of a particular outcome? Here are several definition:

Characteristics of a Cause

To be a cause, the factor:

• Must precede the effect
• Can be either a host or environmental factor (e.g., characteristics, conditions, actions of individuals, events, natural, social or economic phenomena)
• May be positive (presence of a causative exposure) or negative (lack of a preventive exposure)

Risk Factors versus Causes

Epidemiologists often use the term "risk factor" to indicate a factor that is associated with a given outcome. However, a risk factor is not necessarily a cause. The term risk factor includes surrogates for underlying causes. For example, consider the following table which summarizes characteristics associated with a high risk of breast cancer and characteristics associated with a low risk.

Each of these factors (place of birth, socioeconomic status, and marital status) is associated with an increased risk of breast cancer, but none of these are causes. [Recall Susser's definition that a cause is something that makes a difference; or recall Rothman's definition, i.e., that a cause is an event, condition, or characteristic without which the disease would not have occurred.] These risk factors are surrogates or markers for underlying causes, e.g., populations with a higher prevalence of genetic risk from BRCA1 and BRCA2 alleles, or lower parity which in turn is a marker for unopposed estrogen stimulation of breast tissue.) Being born in northern Europe per se is not a cause; it is a marker for populations that may have a greater genetic predisposition to breast cancer.

It is therefore important to distinguish between risk factors and causes. Nevertheless, before one can wrestle with the difficult question of causation, it is first necessary to establish that a valid association exists. Consequently, if we accept Susser's assertion that a cause is something that makes a difference, one might then ask how to tell if a factor makes a difference. Most epidemiologists would agree that, in a broad sense, this is a two step process.

1. The evidence must be examined to determine that there is a valid association between an exposure and an outcome. This is achieved by conducting epidemiologic studies and critically reviewing the available studies to determine whether random error or bias or confounding might explain the apparent association.
2. If it is determined that there is a valid association, then one must wrestle with the question of whether the association was causal. Not all associations are causal. There are no standardized rules for determining whether a relationship is causal.

Answering the question of whether a given factor is a cause or not requires making a judgment. There are no rigid criteria for determining whether a causal relationship exists, although there are guidelines that should be considered. The process of determining whether a causal relationship does in fact exist is called "causal inference".

Given the lack of rigid criteria, debate and disagreement over the evidence is inevitable and positive. However, it also means that the debate can be prolonged for reasons other than scientific dispute, for example, if powerful institutions perceive that there are substantial financial implications that would follow from concluding that there is a causal connection. The existence, sources, and implications of global climate change is perhaps the most prominent current example in which concerns have been raised that commercial interests over the causal association between human activity and atmospheric change have affected the scientific process. The most well-known and well-documented example in recent history was the tobacco industry's effort to deny that the association between cigarette smoking and lung cancer was causal.

The recent Australian elections, which used paper ballots, got us thinking about the advantages and disadvantages of digital voting. Electronic voting advocates point out a number of very useful improvements to the process of voting. E-voting offers greater simplicity in terms of time and effort. It has the potential to improve the number of people voting in remote areas. It can speed up the voting process and also has the capacity to enable citizens who are disabled or who are out of the country, to vote more easily.

It has also been claimed that going digital will encourage millennials, who are the most accustomed to digital technology, to vote. Although, no particular studies have been cited to back this up.

The reality is there is no free lunch. E-voting offers surface simplicity and background complexity. It's simple in that voting becomes easier. People don't have to drive to polling places, registration can be as undemanding as filling out an online form and the votes are automatically counted. The complexity is in the way the votes are counted. The big problem is that the votes are not counted by humans who can be checked by other humans. They are counted digitally. Some would say that this places an inordinate amount of trust in the software. After all, software often has bugs or can malfunction under circumstances not anticipated by testing. Even deployed software should be field tested again from time to time.

But, paper ballots have problems too, as the infamous “hanging chad” incident in the 2000 American presidential election has shown. Paper ballots are complex on the surface. They require a considerable amount of human effort as someone has to physically count each ballot. But, they are simple underneath. It doesn't require a computer science degree to detect if something is wrong, and fraud is harder to hide.

There is little doubt that the transition to digital voting would be a bit costly at the start, although this could be minimized by using established infrastructure like the Internet or phones and avoiding the creation of purpose specific hardware like voting machines. E-voting is certainly possible and may even be a good idea, as long as it is a system that provides equal access to all with the greatest possible security.