On Clonal Selection.

Clonal selection has been a dominant theme in many immune-inspired algorithms applied to machine learning and optimisation. We examine existing clonal selections algorithms for learning from a theoertical and empirical perspective and assert that the widely accepted computational interpretation of clonal selection is compromised both algorithmically andbiologically. We suggest a more capable abstraction of the clonal selection principle grounded in probabilistic estimation and approximation and demonstrate how it addresses some of the shortcomings in existing algorithms. We further show that by recasting black-box optimisation as a learning problem, the same abstraction may be re-employed; thereby taking steps toward unifying the clonal selection principle and distinguishing it from natural selection.

Using Social Media Content for Screening in Recruitment and Selection: Pros and Cons.

The article considers the arguments that have been made in defence of social media screening as well as issues that arise and may effectively erode the reliability and utility of such data for employers. First, the authors consider existing legal frameworks and guidelines that exist in the UK and the USA, as well as the subsequent ethical concerns that arise when employers access and use social networking content for employment purposes. Second, several arguments in favour of the use of social networking content are made, each of which is considered from several angles, including concerns about impression management, bias and discrimination, data protection and security. Ultimately, the current state of knowledge does not provide a definite answer as to whether information from social networks is helpful in recruitment and selection.