# Measuring Ethical Values with AI for Better Teamwork
## 4 Discussion and Conclusions
### Limitations and Future Research  
The work presented is subject to limitations that should be addressed in future studies. Primarily, the results of this work are limited by the small amount of data as well as the methodology. Both the developed ML models for the prediction of personalities and for the prediction of job performance are based on small data sets. Consequently, this limits the generalization of the ML models and the results so that they may not present a general picture. The current work should be replicated on a wider scale with more data in the future to uncover more general models and outcomes. The limitations of our datasets also restricted our choice of model architecture, as one dataset predicted personal values from honest signals computed from email, and a second dataset compared email honest signals with individual and team performance. We hope that in future work, we will be able to obtain a combined dataset that includes all three variables, email, personal values, and individual and business performance. Another data restriction is the collection of subjective data. Though the applied surveys are scientifically validated and widely distributed, the gathered data are self-reported and biased. Because of the biased data, ML may yield prediction models that are biased with inferior accuracy on real-world data [54; 55]. Therefore, future research should focus on gathering data through more objective personality assessment methods. For example, there are real-life virtual simulations in which individuals go through various tasks to assess personality traits based on the individuals' choices during the tasks [56]. As also the performance ratings are not based on objective indicators, the research could also be replicated with objective key performance indicators. Furthermore, the present analysis is limited to the network of email data. Though emails fulfill the purpose of social networks, future research might expand the current study and approach to include other networks, such as LinkedIn or Slack [57]. Another limitation is given by the focus on personality and morality factors, as measured by the four surveys of NEO FFI-R, Moral Foundations questionnaire, Schwartz's Values survey, and DOSPERT. Though the applied surveys cover many different traits, it is suggested that in future research, further personal or moral values should be tested. As an extension, future research, for example, might use the Valued Living Questionnaire, which examines people's value systems and looks at people's values from a different viewpoint than the surveys in the current study [58]. Further, there are limitations in the methodology and modeling process. First, no control variables are observed, and the relationship between job performance and personal characteristics is simplified. Therefore, no clear statement regarding additional contextual factors which affect job performance in addition to the studied traits can be made. There may be additional explanatory variables and circumstances which contribute to the explanatory power of the results. Furthermore, the term job performance is generalized to different performance metrics of different industries and practices. Consequently, identified effects of this study may not be applicable to all industries. However, the study can be repeated, this time focusing on specific indicators of job performance and other explanatory variables, such as job requirements, age, or tenure, to provide more detailed explanations. For the differential effects of perceptions and likelihoods of risk-taking in certain domains on job performance, this research has not provided clear effects or possible explanations and brings the following limitations. First, the implied result of general risk-taking should be viewed with caution. There is a need for more research here since the observations do not quantify whether people profit from risk-taking in the workplace, whether they effectively take risks, or whether they are foolish about taking risks on the job.