The rapid development in computing hardware, and sensor and user interface technologies enable the creation of more and more powerful computing solutions. Mobile, IoT, wearable and ubiquitous systems are designed to help us in our everyday life as well as in any profession. They heavily use machine learning components to automate and provide intelligent features. When working in concert with robot technology the solutions can also physically act in the world.

Software engineers developing such solutions are faced with a range of challenges to create useful solutions that consistently help users wherever they go, at an affordable cost and with a variety of hardware configurations. This means that successful solutions must deliver functionality that adapt to available resources at a given moment, e.g., in terms of sensor data accuracy, available energy, user interface options, processing power and communication options. To remain lawful, they also need protect privacy.

In this DIREC talk Mikkel Baun Kjærgaard will present and discuss engineering tactics to address such concerns and open-source software technologies that help implement tactics in practice. The tactics and software technologies are the result of more than 15 years of use-inspired basic research in projects with heavy industry involvement. The talk will give examples of ongoing projects researching tactics and software technologies for the design of systems with robotic elements. The talk will conclude with directions for future research.

Computer Science deals with the theory and methods for designing, analyzing and engineering systems of data and processes used by and impacting people and the society in which they are embedded. An important ingredient is the development of formal languages and structures for describing data and processes that can at the same time capture the complexity of the problem domain and be subject for analysis and execution by computers.

As the technology and use of computers has evolved and changed over time, a plethora of different languages and structures have been introduced.

Mirroring the evolution from centralized computer systems used mainly for business processes and research to ubiquitous, distributed systems handling processes spanning both our professional and private lives, a key challenge has become the design, analysis and management of distributed and frequently changing structures of data and processes and the regulations and rules they are supposed to follow.

Concretely, Thomas Hildebrandt will present the theory and tools of Dynamic Condition Response (DCR) Graph and give concrete examples of the modelling of legal regulations, rules and processes. The theory and tools are the result of more than 15 years of research and development jointly with industry and public organizations culminating in the establishment of the company DCRSolutions.net in 2018 providing industrial strength tools for design, analysis and execution of decision and process models, which has so far been embedded in the widely used WorkZone enterprise information management system from KMD/NEC as well as open source case management systems used in municipalities in Denmark.

The talk will conclude with directions for current and future research, including the relation between explainable AI and DCR graphs and the award winning process mining based on DCR Graphs and how to represent more general knowledge of organisations which is currently peaking several of Gartner’s hype curves (e.g. Emergent Technologies and Government Technologies and AI) under the terms like Human-centered AI, knowledge graphs, decision intelligence and Digital twins of Government.

In this DIREC talk Kim Guldstrand Larsen will present and discuss how to combine formal verification and AI in order to obtain optimal AND guaranteed safe strategies.

The ultimate goal of synthesis is to disrupt traditional software development. Rather than tedious manual programming with endless testing and revision effort, synthesis comes with the promise of automatic correct-by-construction control software.

In formal verification synthesis has a long history for discrete systems dating back to Church’s problem concerning realization of logic specifications by automata. Within AI the use of (deep) reinforcement learning (Q- and M-learning) has emerged as a popular method for learning optimal control strategies through training, e.g. as applied by autonomous driving.

The formal verification approach and the AI approach to synthesis are highly complementary: Formal verification synthesis comes with absolute guarantees but are computationally expensive with resulting strategies being extremely large. In contrast, AI synthesis comes with no guarantees but is highly scalable with neural networks providing compact strategy representation.

Kim Guldstrand Larsen will present the tool UPPAAL Stratego that combines symbolic techniques with reinforcement learning to achieve (near-)optimality and safety for hybrid Markov decision processes and highlight some of the applications that include water management, traffic light control, and energy aware building.

Emphasis will be on the challenges of implementing learning algorithms, argue for their convergence and designing data structures for compact and understandable strategy representation.

In 2015, only 10% of students on ITU’s Bachelor of Software Development were women. ITU decided to do something about this and a number of initiatives were launched. Now, the percentage of women has risen to 23% (in 2020). We will present an overview of ITU’s efforts to address this gender imbalance in computing.

Also, we will present brand new research on how to change educational activities so that they appeal more to women.

Finally, we will show the effect of ITU’s onboarding initiative BootIT and how this connects with increasing diversity.

This talk will present situations where technological feasibility, accompanied with appropriate theory-of-computation reasoning, impacts not only specific laws and regulations, but also some basic legal doctrines. Specifically, these are situations where justified secrecy and privacy rights regarding sensitive information is pitted against equally justified transparency, accountability, and due process rights pertaining to the same information.

Current legal doctrines accept the seemingly inevitable reality the not all rights can be honored, and instead aim at   “balancing the harms” on all sides.   In sharp contrast, cryptographic concepts such as Zero-Knowledge Proofs and Secure Multi-Party Computation enable legal processes that do honor all rights. 

Moreover, these technologies enable fine-grained delineation of what partial information should be disclosed and to whom, thus opening the door to more nimble legal doctrines and thinking regarding the ownership, sharing, and use of information in a modern society.

The talk will be mostly based on the following two papers:

• Kenneth Bamberger, -, Shafi Goldwasser,  Rebecca Wexler, Evan Zimmerman:  Verification Dilemmas in Law and the Promise of Zero-Knowledge Proofs.  Berkeley Technology Law Journal, Vol. 37, No. 1 (2022).
• Dor Bitan, -, Shafi Goldwasser, Rebecca Wexler: Using Zero-Knowledge to Reconcile Law Enforcement Secrecy and Fair Trial Rights in Criminal Cases. SSRN  (2022).

Tracking detailed interaction behaviour from this number of people results in truly massive datasets. With the rapid growth and innovation in the sector, data has come to the forefront as a means for informing decision making. This has in turn spurred the evolution of the domain of Game Data Science – a cross-disciplinary area that merges perspectives from multiple academic domains to help the Creative Industries make sense – and use – of the rapidly growing data space. Given the constant changes in games, the people who play them and the communities that support them, data from games tend to be volatile, requiring that they be acted on rapidly.

In addition to supporting the industry, the data from video games and gamified applications has permitted Game Data Science to target a broad variety of research questions, from exploring human behaviour to developing new algorithms for real-time analytics, as well as exploring mental health and global cultural shifts.

Game Data Science has had a direct impact on the interactive entertainment industry within the past few years, as the practice of tracking and analysing the behaviour of players and processes has emerged as a key component of game development in this age of mobile platforms, increased game persistence and non-retail-based revenue models.

In this DIREC Talk, Anders Drachen will dive into Game Data Science, explaining what makes games unique and the changes in the industry that build them. A central focus of the presentation will be the user, the player, who is alfa and omega for the success of games, whether they are intended for entertainment or educational purposes.

Drachen will also cover:

• the brief but turbulent history of data science applied in games.
• the current state of the art in the sector.
• the fundamental approaches toward problem-solving and the knowledge discovery process inherent in the domain.
• examples of how Game Data Science operates in practice. The Innovate UK Demonstrator Project Weavr will be presented, which has delivered ground-breaking new data-driven visualisations to esports stakeholders.

Key takeaways from this DIREC Talk

• An overview of the role of data science in the games industry
• Some of the cross-disciplinary challenges and opportunities that have emerged in this fast-evolving area

The distance framework from 2000 has been fundamental to how we think about the design and use of technology supporting cooperative work. In 2014, the framework was changed due to new technological opportunities. With corona, the challenges embedded in distributed work changed again in 2020 and now, after the pandemic, we have a situation where organizations think about how to utilize the learnings from the pandemic in the future workplace.

Professor Pernille Bjørn from University of Copenhagen will take us though the different frameworks and discuss the fundamental challenges in distributed and hybrid work before she presents potential ideas for how to move forward in an organization in terms of future work situations.