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Collective Intelligence: Solving Problems at Scale 23.10.2018

- October 22, 2018 in Events, Featured, ResponsiveOrg Finland

Tuesday 23.10.2018 16:30-18:30 Maria 01/Classroom: https://www.facebook.com/events/321675121922917/
Professor Thomas Malone from MIT, author of the book Superminds – The Suprising Power of People and Computers Thinking Together, defines Collective Intelligence as “the result of groups of individuals acting together in ways that seem intelligent.”
Collective Intelligence is nothing new. In nature we see superorganisms like ant colonies that are able to coordinate their collective efforts without centralized overview. Humanity has developed their own models of Collective Intelligence that have, according to Malone, taken for example the forms of hiearchies, democracies, markets, collectives and ecosystems. However, with the rise of connected technologies based on the Internet, data, AI, IoT and Blockchains to start with, the issue of creating new forms of Collective Intelligence has risen. As Thomas Malone puts it:
“How can people and computers be connected so that—collectively—they act more intelligently than any person, group, or computer has ever done before?”
We are starting to have very diverse examples of this phenomenon ranging from Open Source communities, Amazon’s Mechanical Turk that organizes crowds to work on repetitive tasks, Google’s search engine which uses AI and clicks done by humans to prioritize search results and the largest encyclopedia ever made in Wikipedia. But what we don’t have yet is a general understanding on what makes people and machines work together in the best possible ways and how to harness that knowledge to solving problems at scale. I was privileged to be invited to and participate in Nesta’s event Designing collective intelligence – Mobilising humans and machines to address social needs which sought to bring together the community of people working around the topic. You can check out the presentation materials here:
How might we promote the advancement of Collective Intelligence here in Finland?

This is the topic of our Collective Intelligence – Solving Problems at Scale event. You’re welcome to join in on Tuesday 23.10.2018 16:30-18:30 at Maria 01/Classroom. Facebook event: https://www.facebook.com/events/321675121922917/ You might have stumbled into a competition where people are asked to guess the amount of candy in a large jar. Mysteriously, the average of all the people guessing turns out to be pretty close. You’ve heard the old phrase: the smartest person in the room is the room. On the other hand, computers beat humans in simple, repetitive tasks at scale but humans tend to be more creative. What a combination it would be if we had the ability to harness crowds and operate both at scale and in a creative manner? Nowadays drones are used in humanitarian crises such as hurricane relief to help with mapping areas in need of human assistance. A global, internet-enabled network of digital humanitarians is then used to do analysis of the footage to help with coordination efforts. What if we could create organizations that were able to describe the tasks that need to be done to fulfil a purpose and distribute those tasks to a global network of freelancers that never sleeps? Welcome to an evening of an intro into Collective Intelligence: Solving Problems at Scale hosted by Open Knowledge Finland’s Mikael Seppälä. Learn what it is and discuss where we might see the first examples of it in Finland. Collective Intelligence is one of those rising multidisciplinary approaches that seeks to utilize different types of crowds, machines and enable collaboration that far exceeds the forms of collaboration we see today. You can be a social scientist, a facilitator, a designer, a data scientist or just someone interested in budding forms of collaboration. Sources: Geoff Mulgan: Big Mind: How Collective Intelligence Can Change Our World Nesta: Designing collective intelligence – Mobilising humans and machines to address social needs (event) SAGE Publication’s new journal on Collective Intelligence Collective Intelligence 2018: From Open Knowledge and Network Organizations to Technology-enabled Intelligence Tietoasiantuntija 2-3/2018: Inhimillisyyden ja teknologian liitto johdattaa työn uudelle aikakaudelle The post Collective Intelligence: Solving Problems at Scale 23.10.2018 appeared first on Open Knowledge Finland.

Collective Intelligence 2018: From Open Knowledge and Network Organizations to Technology-enabled Intelligence

- July 11, 2018 in blog, projects, ResponsiveOrg Finland

This article is reposted here from the ResponsiveOrg Finland blog on Medium. I attended the Collective Intelligence 2018 conference was organized 7–8.7.2018 at the University of Zurich, the university where Albert Einstein received his PhD. Most of the participants of the Collective Intelligence 2018 conference were academics and the presentations reflected this but there were a few gems in there that I’d like to elaborate on. What is Collective Intelligence? Collective Intelligence is the promise of intelligence that can exceed the intelligence created at individual, team and organizational levels. It’s a multidisciplinary approach still in its infancy that builds upon better social practices and/or current and emerging combinations of technologies allow us to transcend our limited perspectives and the biases related to them and bundle together the efforts of as many people that we can get to participate in a purposeful manner by means of organizing as a network. Collective Intelligence is both an applied and scientific field. In terms of applied collective intelligence, Geoff Mulgan, the CEO of UK-based Nesta, author of the book Big Mind — How Collective Intelligence Can Change Our World, mentions Wikipedia and Waze as examples. Wikipedia has become the largest encyclopedia ever by means of building a digital platform and having mostly volunteers governing, moderating and editing it. Waze is a route-mapping application that combines the aggregated GPS sensor data of its users to provide route information that can take real-time traffic information into account when suggesting routes. These are examples of technology-enabled Collective Intelligence. Picture source: Collective Intelligence/Wikipedia Social processes of creating information and enabling action are also very difficult when agreement and certainty falter. When this happens, you know you are dealing with a complex topic and that is ambiguous, has many perspectives and local optimum answer to it. In facilitation, this area is called “the Groan Zone” because of the feelings that can and often do arise in it. The processes by which a map of the domain, task or mission in question can be developed socially are another form of Collective Intelligence. In addition to technologies (software-hardware), social groups, forms of data and knowledge are also key enablers of Collective Intelligence. For us Open Knowledge Finland folks, this area is a given of course. Patrick Meier and Drone Video Aid for Disaster Areas The first keynote from Patrick Meier of WeRobotics was mindblowing. Patrick is part of the Digital Humanitarians Network which seeks to promote the use of technology in disaster areas. Patrick’s company’s focus is in drone-assisted aid. Some examples of his projects include:
  1. Founding and facilitating the work of local drone “Flying Labs” in disaster and potential disaster areas:
Because disaster areas require a lot of effort, aid workers are working 20 hour days in situations of crisis. One form of aid is to evaluate where aid is needed and this is done by exploring villages and cities for damaged buildings. This has traditionally been done by sending people to the places and have them evaluate the situations. Patrick Meier’s drones have been used to make this process faster by recording videos of the damaged areas. However because of the dire situation in the crisis areas, evaluation of drone footage was not a priority to air workers. However, by the help of the Digital Humanitarians Network, it is possible to crowdsource the online evaluations of damage based on the drone footage. This, in itself is a great example of Collective Intelligence. The Digital Humanitarians Network is going even further. Because evaluations are being done online, it is possible to use the human-generated evaluation data to train Machine Learning algorithms that might help make the evaluations even faster in the future.
  1. Using AI to augment human observations and scale observation making:
I suggest looking into Patrick’s work, there’s some really inspiring stuff there! Follow Patrick Meier on Twitter: https://twitter.com/PatrickMeier WeRobotics company: https://werobotics.org/ The Digital Humanitarians book: http://digital-humanitarians.com/ Lucy Fortson and Machine Learning for Citizen Science Another intriguing talk at the conference came from Lucy Fortson who is working for Zooniverse, an online platform by which people can participate in making classifications that assist scientific projects. Examples of Zooniverse projects include Galaxy Zoo, a project for classifying distant galaxies based on astronomical photo and Shakespeare’s World, in which voluteers can help transcribe writings from Shakespeare’s time to help understand history better. Zooniverse is an awesome platform with over 40 million classifications done by 150 000 volunteers. As its goal is to assist science the projects hosted on Zooniverse have produced countless scientific articles, new scientific findings and also allowed some of the volunteers to participate in writing the articles. To further help with the Citizen Science assisted research done on their platform, Zooniverse is also exploring the combination of users and Machine Learning to help create observations that are both precise (human) and broad (AI) to expedite the research projects. Rosy Mondardini, Citizen Science and Sustainable Development Goals Rosy Mondardini, leader of the Citizen Science Center at the University of Zurich, had an interesting short talk during a panel on Crowdsourcing and Crowd-Driven Innovation about how they are promoting the use of Citizen Science to measure Sustainable Development Goals. For those not familiar, Sustainable Development Goals are UN’s call to action “to end poverty, protect the planet and ensure prosperity for all that could be achieved in 15 years if all sectors of society would collaborate around them. According to Rosy Mondardini, there is insufficient data to see progress in the Sustainable Development goals and this is one of the areas of opportunity where Citizen Science and crowd-driven coordination might be of assistance. For me, this is an interesting concept in terms enabling future forms of participation in cities. Traditionally data regarding cities has been expert-generated but what if Citizens also had the ability to generate both hard sensor data and soft experiental data about their lived environments to assist in sensemaking and participating in making cities based on their own experiences? Collective Intelligence 2018: Summa Summarum Collective Intelligence is definitely one of those emergent topics that is on the rise even though it seems like the concept is not very well known here in Finland even though we are doing many cool things in the areas of Citizen Science and Open Collaboration. I have not heard of many instances from Finland where technology has been used to augment people in service of large social issues quite yet. Like I mentioned earlier, the Collective Intelligence 2018 conference, even though it had the goal of bringing together practitioners, companies and academics, was not able to cater to the goal and focused mostly on academic approaches. Another issue I had with the conference was the the high focus on technology-enabled collaboration whereas the human-centered approaches having to do with facilitation of groups was mostly missing. Being a person of multiple interests, what I really enjoyed in the conference, was becoming influenced by thinking that is somewhat different than my own. Even though I’m not very deep into Collective Intelligence quite yet, I believe I will be considering options more from the angle of enabling technology-assisted open crowds in my future thinking. In regards to the relationship between what we call Responsive Organizations and Collective Intelligence, I believe we’re in the same ballpark. As Collective Intelligence is the emergent property of the collaboration between groups, technologies and data/knowledge, it shares the same resources as Responsive Organizations. Collective Intelligence, Social Technologies and Network Organizations are heavily related and enablers of each other. Whereas Responsive Organizations use Social Technologies (essentially practices and technologies that allow us to collaborate better and at scale) to organize as scalable Networks or Network Organizations for purposeful action by means of broad knowledge creation, Collective Intelligence is the knowledge that is created using Networks and Social Technologies. They are definitely related concepts. Collective Intelligence is also close to what we call Open Knowledge as the openness of knowledge is an enabler of its purposeful transformation into Collective Intelligence. We at Open Knowledge Finland and ResponsiveOrg Finland will definitely be following the Collective Intelligence scene and hope to promote its practical advancements for the development of the Finnish society.
ResponsiveOrg Finland invites you to explore and promote practices by which teams and organizations can be better at responsiveness to changes, people, futures and operating as a network. Join in: Facebook: https://www.facebook.com/groups/ResponsiveOrgFI/
Twitter: https://twitter.com/ResponsiveOrgFI
WWW: http://responsiveorg.fi
Contact: @mikaelseppala
@OKFFI The post Collective Intelligence 2018: From Open Knowledge and Network Organizations to Technology-enabled Intelligence appeared first on Open Knowledge Finland.

Collective Intelligence 2018: From Open Knowledge and Network Organizations to Technology-enabled Intelligence

- July 11, 2018 in blog, projects, ResponsiveOrg Finland

This article is reposted here from the ResponsiveOrg Finland blog on Medium. I attended the Collective Intelligence 2018 conference was organized 7–8.7.2018 at the University of Zurich, the university where Albert Einstein received his PhD. Most of the participants of the Collective Intelligence 2018 conference were academics and the presentations reflected this but there were a few gems in there that I’d like to elaborate on. What is Collective Intelligence? Collective Intelligence is the promise of intelligence that can exceed the intelligence created at individual, team and organizational levels. It’s a multidisciplinary approach still in its infancy that builds upon better social practices and/or current and emerging combinations of technologies allow us to transcend our limited perspectives and the biases related to them and bundle together the efforts of as many people that we can get to participate in a purposeful manner by means of organizing as a network. Collective Intelligence is both an applied and scientific field. In terms of applied collective intelligence, Geoff Mulgan, the CEO of UK-based Nesta, author of the book Big Mind — How Collective Intelligence Can Change Our World, mentions Wikipedia and Waze as examples. Wikipedia has become the largest encyclopedia ever by means of building a digital platform and having mostly volunteers governing, moderating and editing it. Waze is a route-mapping application that combines the aggregated GPS sensor data of its users to provide route information that can take real-time traffic information into account when suggesting routes. These are examples of technology-enabled Collective Intelligence. Picture source: Collective Intelligence/Wikipedia Social processes of creating information and enabling action are also very difficult when agreement and certainty falter. When this happens, you know you are dealing with a complex topic and that is ambiguous, has many perspectives and local optimum answer to it. In facilitation, this area is called “the Groan Zone” because of the feelings that can and often do arise in it. The processes by which a map of the domain, task or mission in question can be developed socially are another form of Collective Intelligence. In addition to technologies (software-hardware), social groups, forms of data and knowledge are also key enablers of Collective Intelligence. For us Open Knowledge Finland folks, this area is a given of course. Patrick Meier and Drone Video Aid for Disaster Areas The first keynote from Patrick Meier of WeRobotics was mindblowing. Patrick is part of the Digital Humanitarians Network which seeks to promote the use of technology in disaster areas. Patrick’s company’s focus is in drone-assisted aid. Some examples of his projects include:
  1. Founding and facilitating the work of local drone “Flying Labs” in disaster and potential disaster areas:
Because disaster areas require a lot of effort, aid workers are working 20 hour days in situations of crisis. One form of aid is to evaluate where aid is needed and this is done by exploring villages and cities for damaged buildings. This has traditionally been done by sending people to the places and have them evaluate the situations. Patrick Meier’s drones have been used to make this process faster by recording videos of the damaged areas. However because of the dire situation in the crisis areas, evaluation of drone footage was not a priority to air workers. However, by the help of the Digital Humanitarians Network, it is possible to crowdsource the online evaluations of damage based on the drone footage. This, in itself is a great example of Collective Intelligence. The Digital Humanitarians Network is going even further. Because evaluations are being done online, it is possible to use the human-generated evaluation data to train Machine Learning algorithms that might help make the evaluations even faster in the future.
  1. Using AI to augment human observations and scale observation making:
I suggest looking into Patrick’s work, there’s some really inspiring stuff there! Follow Patrick Meier on Twitter: https://twitter.com/PatrickMeier WeRobotics company: https://werobotics.org/ The Digital Humanitarians book: http://digital-humanitarians.com/ Lucy Fortson and Machine Learning for Citizen Science Another intriguing talk at the conference came from Lucy Fortson who is working for Zooniverse, an online platform by which people can participate in making classifications that assist scientific projects. Examples of Zooniverse projects include Galaxy Zoo, a project for classifying distant galaxies based on astronomical photo and Shakespeare’s World, in which voluteers can help transcribe writings from Shakespeare’s time to help understand history better. Zooniverse is an awesome platform with over 40 million classifications done by 150 000 volunteers. As its goal is to assist science the projects hosted on Zooniverse have produced countless scientific articles, new scientific findings and also allowed some of the volunteers to participate in writing the articles. To further help with the Citizen Science assisted research done on their platform, Zooniverse is also exploring the combination of users and Machine Learning to help create observations that are both precise (human) and broad (AI) to expedite the research projects. Rosy Mondardini, Citizen Science and Sustainable Development Goals Rosy Mondardini, leader of the Citizen Science Center at the University of Zurich, had an interesting short talk during a panel on Crowdsourcing and Crowd-Driven Innovation about how they are promoting the use of Citizen Science to measure Sustainable Development Goals. For those not familiar, Sustainable Development Goals are UN’s call to action “to end poverty, protect the planet and ensure prosperity for all that could be achieved in 15 years if all sectors of society would collaborate around them. According to Rosy Mondardini, there is insufficient data to see progress in the Sustainable Development goals and this is one of the areas of opportunity where Citizen Science and crowd-driven coordination might be of assistance. For me, this is an interesting concept in terms enabling future forms of participation in cities. Traditionally data regarding cities has been expert-generated but what if Citizens also had the ability to generate both hard sensor data and soft experiental data about their lived environments to assist in sensemaking and participating in making cities based on their own experiences? Collective Intelligence 2018: Summa Summarum Collective Intelligence is definitely one of those emergent topics that is on the rise even though it seems like the concept is not very well known here in Finland even though we are doing many cool things in the areas of Citizen Science and Open Collaboration. I have not heard of many instances from Finland where technology has been used to augment people in service of large social issues quite yet. Like I mentioned earlier, the Collective Intelligence 2018 conference, even though it had the goal of bringing together practitioners, companies and academics, was not able to cater to the goal and focused mostly on academic approaches. Another issue I had with the conference was the the high focus on technology-enabled collaboration whereas the human-centered approaches having to do with facilitation of groups was mostly missing. Being a person of multiple interests, what I really enjoyed in the conference, was becoming influenced by thinking that is somewhat different than my own. Even though I’m not very deep into Collective Intelligence quite yet, I believe I will be considering options more from the angle of enabling technology-assisted open crowds in my future thinking. In regards to the relationship between what we call Responsive Organizations and Collective Intelligence, I believe we’re in the same ballpark. As Collective Intelligence is the emergent property of the collaboration between groups, technologies and data/knowledge, it shares the same resources as Responsive Organizations. Collective Intelligence, Social Technologies and Network Organizations are heavily related and enablers of each other. Whereas Responsive Organizations use Social Technologies (essentially practices and technologies that allow us to collaborate better and at scale) to organize as scalable Networks or Network Organizations for purposeful action by means of broad knowledge creation, Collective Intelligence is the knowledge that is created using Networks and Social Technologies. They are definitely related concepts. Collective Intelligence is also close to what we call Open Knowledge as the openness of knowledge is an enabler of its purposeful transformation into Collective Intelligence. We at Open Knowledge Finland and ResponsiveOrg Finland will definitely be following the Collective Intelligence scene and hope to promote its practical advancements for the development of the Finnish society.
ResponsiveOrg Finland invites you to explore and promote practices by which teams and organizations can be better at responsiveness to changes, people, futures and operating as a network. Join in: Facebook: https://www.facebook.com/groups/ResponsiveOrgFI/
Twitter: https://twitter.com/ResponsiveOrgFI
WWW: http://responsiveorg.fi
Contact: @mikaelseppala
@OKFFI The post Collective Intelligence 2018: From Open Knowledge and Network Organizations to Technology-enabled Intelligence appeared first on Open Knowledge Finland.