I am spending the next two weeks in Brazil visiting colleagues and developing research partnerships. I will deliver two research seminars:
Shaping the Future of Autonomous Systems in Society: Research with Impact
Emerging technologies are fundamentally impacting and transforming all aspects of our society. I am particularly concerned with how technological innovations impact 1) the design of our public institutions, 2) the apparatuses through which we shape, implement, and evaluate public policies, and 3) our governance frameworks for public goods. All indications suggest that we are moving toward a world where autonomous systems will dictate how we interface and interact with other agents and objects in our society. We can take advantage of emerging technologies to make our societies more livable, just, resilient, and sustainable. To realize this future, we need active and sustained engagement by scholars across a myriad of disciplines, especially public policy and management.
Public policy and governance scholars have largely been absent when it comes to engineering efforts related to the design and deployment of autonomous systems and policy debates that will shape their impact on our society. In this talk, I will outline why we need active engagement by public policy and management scholars during phases of autonomous systems development and implementation. Examples will be drawn from over a dozen research engagements that have studied emerging technologies in the public sector, from predictive analytic systems to blockchain, social media platforms, and machine learning algorithms. I will outline key governance dilemmas and policy challenges confronting public agencies as they try to keep up with the rapid pace of technological innovations.
Studying complex phenomena requires us to undertake research that 1) draws on multiple disciplines, 2) engages a diverse group of stakeholders, 3) appreciates a plurality of research approaches, and 4) generates actionable solutions. Executing inter-disciplinary research is no easy feat to accomplish. Researchers face daunting challenges from the onset; beginning with the inception of ideas, continuing to the crafting of problem statements, executing the research process, and then communicating the results via publications in academic and practitioner outlets. However, these challenges should not be viewed as an excuse to abandon inter-disciplinary research in favor of narrowly focused research exercises. Opportunities for use-inspired research will be discussed. In addition, I will present a working model for executing inter-disciplinary research that has served me well. I will openly share some of the trials and tribulations that I have encountered along the way.
Atif Ahmad (University of Melbourne), Jeb Webb (Oceania Cyber Security Centre), James Boorman (Oceania Cyber Security Centre), and I have a new article accepted for publication in Computers & Security.
Advanced persistent threat (APT) is widely acknowledged to be the most sophisticated and potent class of security threat. APT refers to knowledgeable human attackers that are organized, highly sophisticated and motivated to achieve their objectives against a targeted organization(s) over a prolonged period. Strategically-motivated APTs or S-APTs are distinct in that they draw their objectives from the broader strategic agenda of third parties such as criminal syndicates, nation-states, and rival corporations. In this paper we review the use of the term “advanced persistent threat,” and present a formal definition. We then draw on military science, the science of organized conflict, for a theoretical basis to develop a rigorous and holistic model of the stages of an APT operation which we subsequently use to explain how S-APTs execute their strategically motivated operations using tactics, techniques and procedures. Finally, we present a general disinformation model, derived from situation awareness theory, and explain how disinformation can be used to attack the situation awareness and decision making of not only S-APT operators, but also the entities that back them.
Jim Denford (Royal Military College, Canada), Greg Dawson (Arizona State University) and I were pleased to see that our paper was the best paper for the Information Systems division at the Administrative Sciences Association of Canada 2019 Conference.
As artificial intelligence technologies take over larger number of tasks, India will face unique impacts of automation relative to other countries. With its large and young population, advances in AI will affect India in aspects from jobs to quality of life. Incidentally, the Indian economy is currently ill-equipped to face the advent of automation and AI. To read more...
Spatial-Temporal Effect of Household Solid Waste on Illegal Dumping
Illegal dumping is an increasingly costly problem with profoundly negative consequences for the livability and sustainability of our communities. The problem of illegal dumping is particularly acute in the developing world. While the literature is rich in descriptive studies on illegal dumping, few studies leverage large-scale spatial-temporal data through innovative analytical tools to study the actual dynamics of household illegal waste dumping. Our study aims to fill this gap by developing a multilevel theoretical model with which to illustrate the impact of illegal dumping. We explore the spatial-temporal distribution of illegal dumping cases using data mining. Next, we integrate datasets reflecting different levels into a hierarchical data structure organized by membership function. We then use a hierarchical generalized linear model to validate our multilevel model. The results indicate that the spatial factors have a significant relationship with illegal dumping, whereas the direct influence of temporal and community-level factors on illegal dumping is insignificant. Furthermore, the moderating effect of management level and public order on the relationship between spatial features and illegal dumping is significant. Based on our results, we offer several suggestions for preventing illegal dumping.