Piero Fraternali

Politecnico di Milano, Italy

piero.fraternali@polimi.it

The evolution of the net

The mobile web

How many of us use a mobile terminal?

The social web

What do people do online?

Cosa succede in un minuto su internet

How can we make good use of all this?

Maybe helping computers help people

Problems computers cannot solve

When computers were human

Gaspard De Prony, 1794, hires hires hairdressers (unemployed after French revolution; knew only addition and subtraction) to create logarithmic and trigonometric tables. He managed the process by splitting the work into very detailed workflows. (Hairdressers better than mathematicians in arithmetic!)

Human computation

Normally the user queries the computers

What about the computer querying the user?

...or a "crowd "of users?

Early example: CAPTCHA• Stands for “Completely Automated Public

Turing test to tell Computers and Humans Apart”

• Luis von Ahn et al. coined the term in 2000• A Program that can tell

whether a user is a human or a computer

• Humans and machineshave complementaryskills

The disciplines of HC

Forms of HC: crowdsourcing• Crowdsourcing is a distributed model that

assigns tasks traditionally undertaken by employees or contractors to an undefined crowd

– Split the task into micro-tasks– Assign them to performers in the crowd– Collect partial results into the final one

Paid Crowdsourcing: Amazon Mechanical Turk

Forms of HC: GWAPS• Games with a Purpose (GWAPs)

– Exploiting the billions of hours that people spend online playing with computer games to solve complex problems that involve human intelligence [vA06,LvA09].

– Useful tasks are embedded in a playful experience where human judgment is exploited consciously or unconsciously

Types of Games[Luis von Ahn and Laura Dabbish, CACM 2008]

Three generic game structures

• Output agreement: – Type same output

• Input agreement: – Decide if having same input

• Inversion problem: – P1 generates output from input– P2 looks at P1-output and guesses P1-input

Output Agreement: ESP Game• Players look at common input• Need to agree on output

Input Agreement: TagATune• Sometimes difficult to type identical output

(e.g., “describe this song”)• Show same or different input, let users

describe, ask players if they have same input

Inversion Problem: Peekaboom

• Non-symmetric players• Input: Image with word• Player 1 slowly reveals pic• Player 2 tries to guess word

Linguistic games

Life science games

• Combinatorial problems with intractable solutions spaces, in which humans can help the heuristic core in pruning– Protein folding: Proteins fold

from long chains into small balls, each in a very specific shape

– Shape is the lower-energy setting, which the most stable

– Fold shape is very important to understand interactions with out molecules

– Extremely expensive computationally! (too many degrees of freedom)

• A Mason-Pfizer monkey virus retroviral protease was modeled by FoldIT gamers in just three weeks

Forms of HC: social mobilization

• Social Mobilization– Problems with time constraints, where the

efficiency of task spreading and of solution finding is essential

– An example of the problem and of the techniques employed to face it is the Darpa Network Challenge [PRP+10]

– The solution comes from the nature of the reward mechanism and social ties of humans

HC & public resource management

• Objectives– Collect and validate data– Extract information from data– Involve people in resource usage planning and management– Change people’s behavior

• Approaches– Passive: mine information from existing user’s activity traces– Active: engage people in ad hoc tasks

• Ultimate goals – Obtain “better data” for predictive models, planning and

management tool: more accurate, at finer time/space resolution, in real time …

– Take “better decisions”: more participative, less conflicting, capable of promoting social change

Extracting: population dynamics from twitter data

• Problem: obtaining impact of population on territory at high temporal resolution

• Can be used to detect events, estimate water consumption bursts, waste production, etc

• Solution: using low cost geo-localized data sources (e.g., tweets) together with structured and high cost sources (e.g., mobile phone traces)

http://www.streamreasoning.org/demos/london2012

Predicting: snow fall with Flickr images

• Problem: predicting the incidence of natural phenomena using user generated content

• Solution: using Flickr photos tagged with “snow” to estimate snow fall (precision 100% with 7 snow photos)– H Zhang, M Korayem, DJ Crandall, G LeBuhn: Mining

photo-sharing websites to study ecological phenomena. WWW 2012

Involving: social deliberation tools for participatory planning

• Problem: letting a large crowd of citizens propose solutions or deliberate on proposals about public goods

• Solution: large scale deliberation and idea management tools– IdeaScale.com,

MIT’s Deliberatorium…

Geographical Information Systems (GIS) + Crowd

• GeoWeb 2.0: the tools, infrastructures and services for the management of GIS over the Web

• Volunteered Geo Information (VGI): the vision of humans as sensors that voluntarily create, assemble and disseminate Web geo data.

• Participatory GIS (PGIS): points to the social role of GIS to promote the goals of NGOs and groups, especially in developing countries

• Public PGIS: the practice of exploiting GIS to support public participation into decision-making processes, especially in developed countries

Citizens' territory managment

Monitoring waterways: CreekWatch

• Problem: obtain simple yet useful parameters on water shed conditions in a vast territory at low cost

• Solution: geo localized mobile+Web application – Developed at IBM Research Almaden, 4000+ users, 25 countries– The city of San Jose, CA, uses it to prioritize pollution cleanup efforts

• Collected data are found to have good quality

Other community-based PGIS

http://harassmap.org/en/

Participatory zoning project by the Ahorani people, Tiputini Ecuador

Urban games

• "Urban gaming" or "Street Games" are typically multi-player location-based games played out on city streets and built up urban environments [Wikipedia

• Find points of interest• Social analysis• Security analysis• Healthcare• Traffic analysis• Environment analysis• Collect hidden stories• Behavioral analysis• …

U-GWAPS Examples

• Critical City Upload– Encourage people to make new

journeys, use public transportation in a different way, explore new areas

– Extra bonus points for missions, team work, discover mysteries, etc.

• Ecopath– track user's locations of green

activities (riding a bike or recycling trash), connecting these sites to define "paths" of sustainability.

– users compete with friends over territory defined by their paths, thus adding a social gaming context to their actions as they make environmentally responsible choices

Open problems

• Humans, like machines, can make errors– Cognitive bias, fatigue

• Unlike machines humans can cheat– Classification of attacks– Spammer detection

• Quality of output improvement techniques are in use

• Voting schemes• Workers quality modeling and vote weighing (requires

ground truth or machine learning models and iterative / selective labeling of data)

• Micro-flows, worker’s pre-task testing• Task to worker assignment, active learning

Example of ongoing projects

Politecnico di Milano

CUbRIK Project

• FP7 Integrating Project• Goals:

– Advance the architecture of multimedia search

– Exploit the human contribution in problem solving & social innovation

– Promote open-source components

– Start up a search business ecosystem

• http://www.cubrikproject.eu

36

Click-workers + expert crowd for digital humanities research

GWAP for image object extraction

PeakWatch

• Exploiting User Generated Content for Mountain Peak Detection

• Peaks automatically identified from Flickr photos and digital terrain model

• Snow and water availability prediction

46° 0’ 48.51” N7° 48’ 6.62” E

PoliCrowd: a Web 3D PGIS

– Born to promote tourism and cultural heritage– Interaction with user mobile devices for uploading

Points Of interest (POIs)– POIs three-dimensional visualization on World Wind

virtual globe– User collaborative contribution in POIs characterization– Creating, saving and sharing customized maps with the

community– Winner at the NASA

World Wind EU Challenge 2013

Step 1: find a POI & take a picture of it

Step 2: report the details

Step 3: view your report in 2d

.. and in 3d

Step 4: enrich with multimedia material

Step 6: add layers and share your projects

The CrowdSearcher crowd engagement framework

• Post tasks to the crowd of your choice

• Gather & analyze results

Human task design:Tips on workplaces from friends

Human task execution with Facebook, Twitter, Doodle ..

Urbanopoly

• Buy venues, earn money and collect information about your city by playing with the neighborhood around you in Urbanopoly.

• Venues are real places selected from OpenStreetMap: shops, restaurants, monuments, etc.; visit them and discover if they are free. If the venue is free and you have enough money, you can buy it; otherwise, if the venue is owned by another player, you spin the wheel to see what's your destiny.

Web sites

• http://www.iapad.org/multimedia.htm• www.osgeo.org• http://www.centerforcommunitymapping.org/• http://geomobile.como.polimi.it/policrowd• http://www.cefriel.com/urbanopoly• http://www.cubrikproject.eu• http://www.sketchness.com

References• Managing Crowdsourced Human Computation, Panos

Ipeirotis, New York University Praveen Paritosh, Google

• [LvA09] Edith Law and Luis von Ahn. Input-agreement: a new mechanism for collecting data using human computation games. In Proc. CHI 2009, 2009.

• [vA06] Luis von Ahn. Games with a purpose. Computer, 39:92{94, 2006.

• [vAMM+08] Luis von Ahn, Ben Maurer, Colin McMillen, David Abraham, and Manuel Blum. recaptcha: Human-based character recognition via web security measures. Science, 321(5895):1465~1468, 2008.[

References• Galen Pickard, Iyad Rahwan, Wei Pan, Manuel Cebrian, Riley

Crane, Anmol Madan, and Alex Pentland. Time critical social mobilization: The darpa network challenge winning strategy. CoRR, abs/1008.3172, 2010.

• Trant J., Exploring the potential for social tagging and folksonomy in art museums: proof of concept. New Rev. Hypermed. Multimed. 12(1), 83–105

• Firas Khatib et al, Crystal structure of a monomeric retroviral protease solved by protein folding game players, NATURE, 2011

• S. Kim, C. Robson, T. Zimmerman, J. Pierce, and E. M. Haber. Creek watch: pairing usefulness and usability for successful citizen science. In Proceedings of the 29th Int Conf on Human Factors in Computing Systems, pages 2125–2134, New York, NY, 2011.