Genes, free will, and criminal responsibility.

Advances in human genetics have raised the possibility that genetic mechanisms can explain various aspects of human behavior. It has been suggested that such genetic explanations would tend to diminish responsibility for one's actions. In this paper I argue that the genetic approach adds little to our understanding of free will, determinism, and responsibility. Even though human beings are material systems obeying the laws of the physical and biological sciences, their behavior may still be unpredictable and essentially undetermined. Moreover, with few exceptions, behavior influenced by genes is no more deterministic than is behavior influenced by the environment. An analysis of the genetic and environmental influences and the complex interactions between them reveals a certain symmetry between genetic and environmental explanations of behavior. Consequently, any argument concerning the relevance of a genetic excuse to a criminal defense will be equally applicable to an environmental excuse.

Reconsidering genetic antidiscrimination legislation.

In response to the awareness that genetic discrimination is a significant problem, many states have passed or are passing legislation regulating the use of genetic information. Authors discuss the weaknesses as well as the strengths of such legislation, and recommend that the laws be redrafted to prohibit discrimination on the basis of any type of predictive medical information.

Mean genes and the biology of aggression: a critical review of recent animal and human research.

Recent genetic work has suggested that abnormalities in serotonin biochemistry are directly causally linked to aggressive behavior, and there appears to be a consensus in the psychiatric literature that low levels of the serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA) in cerebrospinal fluid are specifically associated with impulsive violent behavior. We review the limitations of the genetic studies and conduct a meta-analysis of 39 studies linking 5-HIAA to aggression in humans. No differences in mean 5-HIAA levels were found between groups of violent impulsive psychiatric patients and groups of subjects diagnosed with other psychiatric or medical conditions not considered to involve violence once these levels had been corrected for three nonpsychiatric sources of variation (age, sex and height). However, mean 5-HIAA levels in both of these groups were lower than the mean corrected level in groups of normal healthy volunteers. The results confirm an association between low 5-HIAA levels and psychiatric disorders, but fail to support any specific relationship between low 5-HIAA levels and impulsive aggression or criminality. It is premature and misleading to speak of "mean genes" (Hen 1996) or a specific neurochemistry of aggressive behavior.

Biases in summary statistics of slopes and intercepts in linear regression with errors in both variables.

Monte Carlo simulations are employed to investigate the bias in linear regression parameters for cases in which both variables are subject to normally distributed errors. Both homoscedastic and heteroscedastic errors are treated. The results show that, in general, the arithmetic mean, geometric mean, and angle mean (tangent of the mean of the arctangents) of the slopes are biased and non-normally distributed. The arithmetic and geometric means of the intercepts are generally biased and non-normally distributed as well. However, for all the cases considered, the medians of the slopes and of the intercepts are found to be unbiased. In view of the non-normal distributions of the slopes and intercepts, a nonparametric method is used to determine confidence intervals for the slopes and intercepts.

Genetic discrimination and screening for hemochromatosis.

Recent advances in tests for the genotype for hemochromatosis and suggestions that the tests be used in mass screening programs for the disease raise the possibility of a large increase in the incidence of discrimination against people who are found to be homozygous for hemochromatosis. This paper presents cases of genetic discrimination drawn from a study of discrimination against people with a variety of genetic conditions. The cases discussed here involve employment and several types of insurance discrimination against people diagnosed with hemochromatosis who either are currently asymptomatic or whose condition is controlled by means of phlebotomies. There is no justification for these types of discrimination since people with controlled hemochromatosis suffer no excess mortality or morbidity. Our study suggests that genetic discrimination is already a serious problem and that any proposed screening program for hemochromatosis or other genetic condition must consider and attempt to mitigate its effects.

Genetic fatalism and social policy: the implications of behavior genetics research.

Recent advances in molecular genetics methods have provided new means of determining the genetic bases of human behavioral traits. The impetus for the use of these approaches for specific behaviors depends, in large part, on previous familial studies on inheritance of such traits. In the past, a finding of a genetic basis for a trait was often accompanied with the idea that that trait is unchangeable. We discuss the definition of "genetic trait" and heritability and examine the relationship between these concepts and the malleability of traits for both molecular and nonmolecular approaches to behavioral genetics. We argue that the malleability of traits is as much a social and political question as it is a biological one and that whether or not a trait is genetic has little relevance to questions concerning determinism, free will, and individual responsibility for actions. We conclude by noting that "scientific objectivity" should not be used to conceal the social perspectives that underlie proposals regarding social change.

On establishing the genetic basis of mental disease.

Many of the recent studies reporting genetic linkages for mental illnesses such as schizophrenia and manic depression have been retracted. The authors of this article argue that the fundamental reason for the difficulties in this research field lies in the strongly held preconceived belief that the primary cause of these illnesses is in fact genetic. All scientists hold preconceived ideas. However, such ideas are more likely to result in erroneous conclusions in the study of human behavior than in other more 'objective' research areas. Moreover, it is especially important that researchers studying human behavior be aware of their biases and learn to compensate for them because of the social consequences of their work.

Genetic discrimination and the public entities and public accommodations Titles of the Americans with Disabilities Act.

The introduction of newly developed medical genetic diagnostic tests has been accompanied by social problems involving privacy issues and genetic discrimination. Previous studies of genetic discrimination have focused on the areas of employment and insurance. In this paper, we provide six hypothetical illustrative cases of genetic discrimination involving access to public entities and to private entities considered to be public accommodations. We argue that many of these forms of genetic discrimination that arise in both the public and private sectors should be prohibited by Titles II and III, respectively, of the Americans with Disabilities Act of 1990.

Application of nonparametric statistics to the estimation of the accuracy of Monte Carlo confidence intervals in regression analysis.

Confidence intervals and their uncertainties for nonlinear regression parameters are obtained using nonparametric statistical methods. The confidence intervals are calculated by means of a Monte Carlo procedure. Their uncertainties depend on the confidence level desired and on the number of Monte Carlo simulations of the data set. They are obtained by calculating the uncertainties in the boundaries of the confidence intervals using a generalization of the nonparametric method used to calculate confidence intervals for medians. The method described here provides reliable confidence intervals at relatively low computational expense. It seems especially suited to the statistical analysis of nonlinear regression problems that are difficult to deal with using conventional methods.