This endeavor focuses on developing tools and cognitive tests to: (1) capture the full range of abilities of autistic adults, and (2) understand and classify the cognitive demands of 21st-century workforce tasks. We seek to characterize the cognitive strengths, unique capabilities, as well as the individual social and cognitive challenges faced by individuals, to develop a quantitative model of what factors are most important for long-term stability and success in the workplace. One example of the type of hypothesis we are investigating is that some high-functioning autistic adults have exceptional visual-spatial abilities that can provide a unique advantage to employers for certain tasks like data visualization (see NASA neurodiversity showcase).
First, we are collecting detailed data from autistic adults using well-validated measures on individual and behavioral functioning (see the Tong Lab), after being offered a job but before they have started that job. For example, recent studies suggest that high-functioning individuals with autism often outperform non-autistic controls at the Raven’s Matrices and other tests of mental imagery and nonverbal reasoning. Additional measures include: 1) adaptive functioning using the Vineland Scales of Adaptive Behavior; 2) depression and anxiety using Beck Depression and Anxiety Inventories; 3) executive functioning using BRIEF; and measures of neurocognitive skill/impairment (IQ, measures of theory of mind). We then prospectively collect measures of occupational success and challenge from individual, co-worker, and manager perspectives during early sustained employment (first six months). We also collect information from employers, and conduct interviews with the ASD employees, at monthly or bi-weekly intervals regarding job performance, hours worked, raises or promotion, issues encountered, etc.
Second, we use computational cognitive systems (see the Kunda AIVAS Lab) as models to explore and elucidate the relationships between cognitive skills, task demands, and the conditions that maximize successful performance on complex, real-world workforce tasks. Cognitive systems are computational models of how intelligent agents combine different cognitive processes, like learning, reasoning, and memory, to perform a task. By implementing cognitive systems that simulate the process of solving various 21st century workforce tasks, we can look “under the hood” at the types of information processing mechanisms that drive successful performance. While these kinds of cognitive systems do not necessarily model every human psychological and neural process, they are extremely valuable for understanding how different cognitive mechanisms contribute to task performance, and how certain cognitive strengths and limitations might affect the likelihood of success. Informed by these computational experiments, we can study particular workforce tasks in more detail and tailor-design technology-based supports that help users improve their cognitive abilities in key employment-relevant areas.
Our research team includes experts in developing cognitive and computational models to characterize these types of exceptional autistic ability, and ways to quantify a person’s core abilities of pattern perception, mental imagery, selective visual attention, and visual working memory. Using a combination of human participant studies and computational modeling experiments as our research methods, we are evaluating these core cognitive measures and their contributions to performance at more complex tasks that are important in the 21st-century workforce setting. The research team also includes experts in the design and administration of standard social and cognitive tests, thus we are also investigating a number of important issues associated with understanding and supporting successful employment of autistic individuals, such as coping with co-morbidities that often accompany autism, including anxiety and depression, and understanding non-disclosure and encouraging individuals toward voluntary disclosure in supportive environments.
Critically, this research seeks to identify what cognitive skills prove most valuable in the workplace. It is possible that greater visual-spatial ability is highly predictive of gainful employment in a particular type of work position. In connection with the research endeavor below, we may find that over longer periods of employment, continued success in various job settings also depends on measures of social awareness, language ability, personal interests, and communication style, as well as on management structure and style. As a result, we will have direct quantitative data demonstrating the cognitive strengths of individuals with ASD, to clarify for potential employers the benefits of hiring individuals with particular talents. Second, we will have a better characterization of the types of work tasks best suited for a particular individual, given their cognitive and social profile as characterized by the measures discussed above. These data will also highlight how an individual will benefit from further training in a particular area, and provide key information for how best to structure their management plan. Third, these cognitive tests and model-based task analysis tools will help lead to the development of web-based assessment and training tools that can be taken online, so that any individual with ASD can assess their abilities and benefit from training in particular cognitive skills.