To create Real AI for Real People in the real world,


The world needs new kinds of real artificial intelligence.

Real AI can use data efficiently and yield results in real-world settings where data is a scarce resource. Real AIs can be trusted to work in an adversarial reality, respect the privacy of people, data and models, and be secure from manipulation and misuse. The third prerequisite for real AI is understandability: the capacity to work with us and augment human abilities, instead of replacing them.

Whoever solves these issues – Data Efficiency, Trust & Ethics, and Understandability – will create the new wave of the AI revolution.


I DATA efficiency

Current AI solutions can be very successful in domains where tasks are relatively simple and well-defined and an abundance of high-quality, properly annotated data are available. Existing AI methods do not, however, easily extend to domains where such data are not available or are difficult or expensive to acquire. Real AIs will be able to work with real-world scarce data – ill-defined, hard to acquire or unavailable.



II Trust and ethics

We will create AIs that are secure, give trustworthy results, preserve privacy, are fair, and whose use is ethically sustainable. We will develop the required privacy-preserving and secure methods to address challenges related to susceptibility to manipulation, information stealing and unethical approaches. We will provide new resilient deep learning approaches for the currently popular and successful deep neural networks.




AI does not yet understand users. We need to open the “black box” of many AI methods: to understand how methods such as neural networks operate and what are the uncertainties inherent to their outputs. Modeling the user and the interaction will help the AI understand the user and vice versa. The outcome is AIs that are able to augment human capabilities in a multitude of tasks.



Currently, FCAI runs five research programs with multiple research groups contributing to each program. The programs do fundamental AI research and reach across a variety of scientific disciplines; groups from multiple fields work together. New openings are constantly sought after and new programs launched on a yearly basis. 


  AI research programs (columns) and the disciplines linked to them (AI Across Fields rows), with expansion plan in colors: currently in operation (dark green), starting in 1–2 years (middle green), and in planning (light green).   (On-going work and initiatives will be linked to from the matrix (work in progress)).

AI research programs (columns) and the disciplines linked to them (AI Across Fields rows), with expansion plan in colors: currently in operation (dark green), starting in 1–2 years (middle green), and in planning (light green). (On-going work and initiatives will be linked to from the matrix (work in progress)).


Agile probabilistic AI

Contributes to objectives I, II and III by developing an interactive and AI-assisted process for building new AI models with practical probabilistic programming. The models will work as explainable, verifiable, uncertainty-aware, reliable tools to build and check the behavior of AIs.

Responsible coordinator: Professor Aki Vehtari, Computer Science (Aalto University)


Simulator-based inference

Contributes to objectives I and III with new methods needed for real AIs to have efficient and interpretable reasoning capabilities. This requires cross-breeding modern machine learning and simulator-based inference.

Responsible coordinator: Professor Jukka Corander, Statistics (University of Helsinki, University of Oslo and Sanger Institute)



Next-generation data-efficient deep learning

Contributes to objectives I and III by developing methods that harness the power of deep learning. These methods include semi-supervised learning, few-shot learning for making use of auxiliary sources of training data, and learning models that can be reliably used in simulator-based inference. The goal is to achieve high-quality results with scarce training data and only limited human supervision.

Responsible coordinator: CEO Harri Valpola (Curious AI)


Privacy-preserving and secure AI

Contributes to objectives I and II with security and privacy research. We develop realistic adversary models to build effective tools and techniques that practitioners can use to build dependable AI systems.

Responsible coordinators: Professor Antti Honkela, Statistics (University of Helsinki) & Professor N. Asokan, Security (Aalto University)



Interactive AI

Contributes to objectives II and III by developing methods for collaborative forms of AI: their ability to infer human beliefs and abilities from observations and predicting the consequences of their actions on humans. These are AIs with which people can naturally work and solve problems, and which demonstrate the ability to better understand our goals and abilities, take initiative more sensitively, align their objectives with us, and support us.

Responsible coordinator: Professor Antti Oulasvirta, HCI, Cognitive Science (Aalto University)


new openings

FCAI research programs are fixed-term and new programs will be launched yearly primed by active scouting by the researchers in the community, and by proactive planning to include missing fields by partnering, networking, and recruiting. Currently, we are preparing to initiate a new research program on Autonomous AI.

The next set of new programs being prepared for consideration involve Ethical and Social Aspects of AI, Multimedia and Computer Vision, and Industrial AI. We also launch annual open calls for the renewal process.

AI ACross fields

In order to maximize the positive impact of AI, we work together with top experts in an increasing number of scientific disciplines, business domains, and societal initiatives. The resulting new insights from each we leverage to inspire new AI methods.

Up to now, FCAI has initiatives in a variety of fields, such as materials physics, social sciences, and economics. The list will be updated constantly, and new ideas and disciplines are welcome to join our common endeavor.

Collaborations between the research programs and accompanying disciplines across fields will yield concrete solutions. They highlight how scientific advances will have direct and tangible societal impact and contribute to economy and well-being.

Academic partnership program

FCAI aims to create a wide ecosystem of partners from academia, industry, and the public sector.

FCAI is not a closed club; we welcome new actors to join the FCAI research programs. FCAI is open for proposals for new activities that are both aligned with its core mission and demonstrate high scientific, economic, or societal impact potential.

In addition to creating collaborations bottom-up, FCAI also maintains institute-level strategic academic partnerships with top-level international partners. They include:

Responsible coordinators for the academic partnership program:
Professor Samuel Kaski (Aalto University)
Professor Petri Myllymäki (University of Helsinki)