Search results for "Tekoäly"
showing 10 items of 188 documents
Subjektin katoamisen uhkakuvat
2021
Arvio teoksesta: Andrejevic, Mark. 2020. Automated Media. New York & London: Routledge, 172 s. publishedVersion Non peer reviewed
Bridging human and machine learning for the needs of collective intelligence development
2020
There are no doubts that artificial and human intelligence enhance and complement each other. They are stronger together as a team of Collective (Collaborative) Intelligence. Both require training for personal development and high performance. However, the approaches to training (human vs. machine learning) are traditionally very different. If one needs efficient hybrid collective intelligence team, e.g. for managing processes within the Industry 4.0, then all the team members have to learn together. In this paper we point out the need for bridging the gap between the human and machine learning, so that some approaches used in machine learning will be useful for humans and vice-versa, some …
ECCOLA : a method for implementing ethically aligned AI systems
2021
Artificial Intelligence (AI) systems are becoming increasingly widespread and exert a growing influence on society at large. The growing impact of these systems has also highlighted potential issues that may arise from their utilization, such as data privacy issues, resulting in calls for ethical AI systems. Yet, how to develop ethical AI systems remains an important question in the area. How should the principles and values be converted into requirements for these systems, and what should developers and the organizations developing these systems do? To further bridge this gap in the area, in this paper, we present a method for implementing AI ethics: ECCOLA. Following a cyclical action res…
Identifying opportunities for AI applications in healthcare — Renewing the national healthcare and social services
2018
A vast variety of artificial intelligence techniques have been deployed to specific healthcare problems during the last thirty years with varying levels of success while there is a shortage of systematic matching of AI capabilities with the breadth of application opportunities. In this paper, we describe the process of identifying opportunities for deploying artificial intelligence to healthcare and social services on regional and national levels in Finland. The project involved a large number of stakeholders from a variety of backgrounds ranging from governmental agencies to entrepreneurs. The process described includes idea generation of an application or solution and its elaboration in w…
Challenge of tacit knowledge in acquiring information in cognitive mimetics
2019
Intelligent technologies are rising. This is why methods for designing them are important. One approach is to study how people process information in carrying out intelligence demanding tasks and use this information in designing new technology solutions. This approach can be called cognitive mimetics. A problem in mimetics is to explicate tacit or subconscious knowledge. Here, we study a combination of thinking aloud in ship simulator driving and focus group commenting the solutions of subjects. On the ground of these early experiments, a multiple method combination seems to be the best way forward to solve problems of tacit or subconscious knowledge. peerReviewed
Tekoäly terveydenhuollossa : katsaus Aasiaan
2018
Erkki Kurenniemi : musiikin ja teknologian avantgardisti
2019
Erkki Kurenniemi (10.7.1941 – 1.5.2017) on kansainvälisesti tunnetuimpia suomalaisia musiikin avantgardisteja. Kuitenkin kesti kauan ennen kuin hänen arvonsa Suomessa tunnustettiin. Vasta 2000-luvulla häntä palkittiin ja hänen tuotantoaan ja toimintaansa alettiin laajemmin tutkia. Kurenniemen toimintakenttä taiteen alalla oli laaja käsittäen elektronisia soittimia ja sävellyksiä, elokuvia, mediataidetta ja tiedefantasioita. Kurenniemi oli koulutukseltaan fyysikko. Tässä artikkelissa luodaan yleiskatsaus Kurenniemen toimintaan ja saavutuksiin musiikin, taiteen ja teknologian aloilla, mutta perehdytään myös hänen teoreettisiin pohdiskeluihinsa, jotka ovat jääneet vähemmälle huomiolle. nonPeer…
Algorithms and Organizing
2022
Abstract Algorithms are a ubiquitous part of organizations as they enable, guide, and restrict organizing at the level of everyday interactions. This essay focuses on algorithms and organizing by reviewing the literature on algorithms in organizations, examining the viewpoint of relationality and relational agency on algorithms and organizing, exploring the properties of algorithms, and concluding what these mean from an organizational communication viewpoint. Algorithms need data to be collected. The data are always biased, and algorithms exclude everything that is not in their code. They define what is seen as important. Their operating principles are opaque, and they are political due to…
Developing Solutions For Healthcare : Deploying Artificial Intelligence to an Evolving Target
2017
—The pace of deploying artificial intelligence (AI) techniques to healthcare has been speeding up. Many of the initiatives have been technology driven aiming at finding problems matching the new technology while systematic, demand driven search for solutions has been limited. Here we describe the process of identifying opportunities for deploying artificial intelligence to healthcare and social services on regional and national levels in Finland. The process includes idea generation and elaboration using a design thinking method complemented with architectural design for identifying required AI capabilities for the 34 best use cases. In this paper, we focus on the development of use case “M…
Instance-Based Multi-Label Classification via Multi-Target Distance Regression
2021
Interest in multi-target regression and multi-label classification techniques and their applications have been increasing lately. Here, we use the distance-based supervised method, minimal learning machine (MLM), as a base model for multi-label classification. We also propose and test a hybridization of unsupervised and supervised techniques, where prototype-based clustering is used to reduce both the training time and the overall model complexity. In computational experiments, competitive or improved quality of the obtained models compared to the state-of-the-art techniques was observed. peerReviewed