Consensus too soon: judges’ and lawyers’ views on genetic information use

Figures & data

Table 1. Gender and age descriptives per group.

Group	Male	Female	Undisclosed	Non-binary	Age
					Mean	SD	Range
Judge	27 (37.0%)	44 (60.3%)	1 (1.4%)	1 (1.4%)	48.50	6.87	34–66
Lawyer	37 (39.4%)	57 (60.6%)	0 (0.0%)	0 (0.0%)	45.23	6.75	21–62
Non-lawyer	38 (32.8%)	77 (66.4%)	1 (0.9%)	0 (0.0%)	35.61	12.57	18–62

Figure 1. In deciding on whether to take a genetic test, which of the considerations below apply to you? Note. Judges N = 73, Lawyers N = 94, Non-lawyers N = 116. The bars represent the percentages responding “yes, this consideration applies to me.”

Table 2. Responses to items about the need to amend relevant laws.

From a DNA sample taken at birth we already can predict, with a degree of probability, future behavior, such as school performance. The precision of prediction is continuously increasing. Moreover, sequencing is already routinely conducted for medical research and other purposes. When should the following laws be updated accordingly?
Data protection and privacy laws
	Now (asap)	After some cases in these areas have been brought to courts	After we are certain of the scale of the risk	No need to do so as the current laws are sufficient
Judge	65 89%	0 0.0%	8 11%	0 0.0%
Lawyers	48 81.4%	4 6.8%	6 10.2%	1 1.7%
Discrimination laws (e.g. education, health benefits, race)
	Now (asap)	After some cases in these areas have been brought to courts	After we are certain of the scale of the risk	No need to do so as the current laws are sufficient
Judge	57 78.1%	5 6.8%	11 15.1%	0 0.0%
Lawyers	41 69.5%	5 8.5%	11 18.6%	2 3.4%
Insurance laws
	Now (asap)	After some cases in these areas have been brought to courts	After we are certain of the scale of the risk	No need to do so as the current laws are sufficient
Judges	53 72.6%	6 8.2%	14 19.2%	0 0.0%
Lawyers	42 71.2%	6 10.2%	11 18.6%	0 0.0%
Employment laws
	Now (asap)	After some cases in these areas have been brought to courts	After we are certain of the scale of the risk	No need to do so as the current laws are sufficient
Judges	54 74%	5 6.8%	14 19.2%	0 0.0%
Lawyers	40 71.4%	5 8.9%	11 19.6%	0 0.0%

Table 3. Vignette 1: compensation for genetic data breaches.

It is now 2020. Mary's genome shows that she has a propensity for a particular type of cancer. Due to earlier data breaches by the national health service, Mary's genetic data had fallen into the possession of insurance companies, from untraceable sources. Mary had applied for health insurance, and had received very high quotes (her genetic propensity not given as a reason), which she could not afford. Mary is now ill and facing very high medical bills. Based on this scenario:
Group	The NHS should compensate Mary, because data were in their possession.	The Government should compensate Mary for not having updated the laws when it became apparent that genetic sequencing was becoming a routine for research and other purposes.	The insurance company should compensate Mary even though their claim is that the data were available online.	No one is responsible, because Mary should have opted out of the research programme.
Judges	37 50.7%	31 42.5%	5 6.8%	0 0.0%
Lawyers	45 47.9%	31 33%	13 13.8%	5 5.3%

Table 4. Vignette 2: breaches of genetic data in employment.

It is 2020. It has now become possible to predict (with a much greater degree of certainty) an individual’s performance from DNA alone. The laws are now updated, making genetic data breaches a criminal offence. However, numerous genetic data breaches had occurred before laws were updated. Employers, who got hold of the data through unknown sources (due to previous breaches), without declaring the basis of the selection, started headhunting people whose genetic codes showed that they would be better performers. People have an action against:
Group	The employers	The Government for not updating in time the laws to prevent genetic data breaches	No-one, as it is the right of employers to choose the most suitable people for the job	No one, because hiring on genetic data produces similar outcome to hiring on test results and curriculum vitae (CV), and is a more efficient way.
Judges	27 37.0%	46 63.0%	0 0.0%	0 0.0%
Lawyers	51 54.3%	41 43.6%	2 2.1%	0 0.0%