Courses

Below you can find a list of all the courses provided by the Collective Intelligence Research Group at ITU.

Collective Intelligence for Predictions, Innovation, Work, and Competitiveness (new course for executives)

The course offers the opportunity to understand and apply collective intelligence and ‘bottom-up’ information aggregation in an organization. The course explores how important stakeholders of an organization (both internal and external “global” crowds) can use platforms collectively to advance creativity, innovation, workflows, and predictions of uncertainties. Collective intelligent tools are already emergent technologies that can help companies to stay agile in the 21st century.

In this course, you will learn to harness tacit knowledge through employee predictions. This will help you as a decision-maker to build a foundation for more accurate information for your decision-making. Thus, you will be able to develop a more competitive organization as you receive accurate information in lead time for your decisions.

You will also learn to harness collective intelligence from internal and external crowds to accelerate the organization’s innovation rate and thereby build new innovative and competitive advantages.

You will learn to crowdsource task solutions from external crowds to expand the skill base of the organization and strengthen agility while reducing costs in the supply chain and building competitiveness.

The course introduces managers to setting up and running ongoing crowdsourcing activities with the purpose of aggregating collective intelligence in crowdsourcing platforms from important stakeholder groups, such as employees, customers, suppliers, and external crowds.

The course builds decision makers’ ability to select, analyze and develop accelerating growth through collective intelligence by adopting:

-   crowdsourcing for predictions
-   crowdsourcing for innovation
-   crowdsourcing for work

The course highlights the important role of users and crowds as an important source of competitive advantage. The course will include various open innovation and crowdsourcing strategies such as:

-   search mechanisms
-   motivational aspects
-   platform assessment
-   crowdsourcing methods

Background

The course starts with the premise of The Fourth Industrial Revolution, which represents a fundamental change in the way we live, work, and relate to one another. It is a new chapter in human development, enabled by extraordinary technological advances commensurate with those of the first, second, and third industrial revolutions. These advances are merging the physical, digital, and biological worlds in ways that create both huge promise and potential peril.

The speed, breadth and depth of this technological revolution are forcing us to rethink how organizations, municipalities, communities and countries create value. For decision-makers, it raises a need for reviewing the logic and practice of current business management in the light of both globalization and the use of technology, but also in transitioning administrative management to smart management and the use of artificial intelligence facilitated by collective intelligence. Further, the networking of companies and the widespread use of knowledge as an intangible asset, such as intuition, sensing and predictions, creativity and insight, will become cornerstones in rethinking and assessing the validity of existing management systems to respond to changes in the business environment and market volatility.

For more information, click here.

Database Use and Design, IT University of Copenhagen

The course gives an introduction and overview of data engineering techniques and practices.

DESCRIPTION

A data ‘revolution’ is underway, a fourth industrial revolution, one that is already reshaping how knowledge is produced, business conducted, and governance enacted. Data has traditionally been time-consuming and costly to generate, analyze, and interpret and generally provided a relatively static and coarse snapshot of phenomena.

This state of affairs is changing now. Rather than being scarce and limited in scope, data production is increasingly becoming a ‘deluge,’ i.e., a vast flow of real-time, varied, resolute, and relational data relatively low in cost. 

Data is increasingly becoming open as well. This data abundance (as opposed to data scarcity) is reshaping how we work with, circulate, trade, analyze, and exploit data. This development is founded on the latest wave of information sources and communication technologies, such as collective intelligence, artificial intelligence/machine learning, big data harvested from social media and the internet, or through the internet of things. Data is produced through mobile phones, distributed and cloud computing, open-source platforms, crowdsourcing platforms, and the plethora of digital devices encountered in homes, workplaces, public spaces, and inter-worked sensors and devices. 

These technical infrastructures lead to evermore aspects of everyday life – work, consumption, travel, communication, and leisure – being captured as data. Moreover, they are re-configuring the production, circulation, and interpretation of data. 

The students will gain an understanding of the technical aspects of data management and the opportunities and risks they create for organizations.

During the course, the students will relate and work with the (changing) nature of database use and design, including:

• Data purpose, representation and modeling 
• Data collection, retrieval, and storage 
• Data Engineering and Data Processes 
• Architecture of Unbundled Data Systems

For more information, click here.

Collective Intelligence: Crowdsourcing for Firm Innovation and Predictions,

Copenhagen Business School

DESCRIPTION

The study of Collective Intelligence; Crowdsourcing for Firm Innovation and Predictions is essentially the study of collective intelligence and ‘bottom-up’ information aggregation from the organization's important stakeholders (both internal and external "global" crowds) for advancing firm creativity, innovation and predictions of uncertainties.

The course builds students’ ability to set up and run ongoing crowdsourcing activities with the purpose of aggregating and using knowledge and collective intelligence from the firms’ important stakeholder groups, such as employees, customers and suppliers, for use in effective strategic decision-making and innovation management. That is, the course builds students’ ability to analyze, select and develop innovation strategies by introducing 'crowdsourcing of innovation', 'prediction markets', 'prediction without markets' as emergent business information aggregation tools to assess changes in the firm’s internal and external environments.

The course starts with the premise that business strategy is a dynamic process that is both reactive and proactive in dealing with ongoing changes and innovation processes within the firm. The course analyzes the phenomenon of collective intelligence and covers various crowdsourcing and prediction mechanisms. That is, the course presents various tools and methods to crowdsource for innovation, creativity, and predictive purposes that can be used to modify, adapt, and change new service designs and other business initiatives that can positively affect the firm’s strategic outcomes.

Crowdsourcing for firm innovation highlights the role of users and “crowds” as an important external source of innovation and will include various open innovation and crowdsourcing strategies, including search mechanisms, motivational aspects, platform assessment and crowdsourcing methods. The course will also include hands-on workshops on how crowds can be used for strategic funding decisions through crowdfunding.

Crowdsourcing of predictions includes 'prediction markets', 'wisdom of crowds' and 'crowd predictions without markets' that involve the assessment of uncertainties in environmental and operational conditions. We will cover voting dynamics, risk management, strategic issue management, prediction of promising projects, and the forecasting of performance metrics, product success and scenarios, natural disasters, terror, and highly uncertain (fuzzy) events, such as changes in the customer, employee satisfaction, and brand reputation.

For more information, click here.