Problem Definition
• Motivation: Policy makers in the area of social service delivery do not have good tools for evaluating the effectiveness of alternative programs before they become policies.
• Goal: Develop a high-fidelity homeless person emulation that can be used in a
simulation environment to evaluate social service policies.
Ziyu Xiao from Beijing, China outlines a community initiative process that includes collecting feedback from communities, conducting surveys and research on issues, developing solutions, implementing programs, tracking outputs and statistics, and evaluating results. The initiative involves community members, volunteers, government, universities, and research institutes at different stages of the process from data collection to evaluation. The overall goal is to facilitate problem solving and actions that improve the community by connecting citizens and society.
Contribution to proactivity in mobile context-aware recommender systemsDaniel Gallego Vico
1) The document proposes methods for incorporating proactivity into mobile context-aware recommender systems (CARS) and evaluates their impact on user experience.
2) An architecture is presented for building social mobile CARS that integrates various social data sources while addressing privacy, cross-platform use, and cold start issues.
3) A model is described for generating proactive recommendations in mobile CARS based on assessing the appropriateness of the user's situation and suitability of item recommendations.
This document proposes a novel social media recruitment technique using machine learning. It involves extracting candidate data from social networking profiles on platforms like LinkedIn, Facebook, and Twitter. This data would then be analyzed using machine learning algorithms like logistic regression to predict the best candidates. The model aims to provide recruiters with a more holistic understanding of candidates compared to traditional recruitment methods. Case studies show this approach can reduce hiring costs and time while increasing hiring manager satisfaction. Future work would involve implementing a prototype and acquiring quality training data.
Knowledge Management in Healthcare AnalyticsGregory Nelson
The promise of actionable analytics in healthcare poses an inherent challenge as we seek to accelerate the time it takes to go from question to insight to action. The velocity of change, the demand for bigger data, the allure of advanced algorithms, the need for deeper insights, and the cost of inaction make knowledge capture and reuse an all too allusive goal.
In an evolving environment, healthcare organizations need to find ways to make greater use of prior investments in analytics products by reusing the commonalities of proven designs, metadata, business rules, captured learnings, and collaborative insights and applying them to future analytics products. By doing so in a strategic manner, they will be able to create rapid and efficient analytics processes and better manage time to value and reuse.
In this presentation, authors from two very different health systems with two very different patient populations will share their perspectives of the value of knowledge management and discuss the role of analytics in driving towards a learning health system. The authors will highlight opportunities and challenges using examples across clinical, financial, and operational domains.
This document outlines a study examining the entrepreneurial relationship development (ERD) capabilities of librarians and how those capabilities support the knowledge economy and socio-cultural changes. It provides background on the changing roles of librarians and defines key terms like knowledge economy and ERD. The study aims to understand librarians' ERD capabilities and how those capabilities enhance the knowledge economy and socio-cultural changes. Preliminary findings suggest that information behaviors and interactive practices positively influence relational capabilities, which in turn positively influence the knowledge economy and socio-cultural changes.
This presentation is by ESN's Policy Director, Alfonso Lara Montero at the Latin American Congress of Social Work in Merida, Spain on 20 October 2017. ESN has run a session on social innovation with ESN members from Belgium and Finland presenting evidence-based social services for children and families.
Presentation by the OECD on the “World Class Civil Service" made at the meeti...OECD Governance
This presentation by Edwin Lau, OECD, on the “WorLd Class Civil Service" was made at the meeting of the OECD Working Party on Public Employment and Management on 20-21 April 2015.
For further on information on the OECD work on Public Employment and Management please see http://www.oecd.org/gov/pem/.
Ziyu Xiao from Beijing, China outlines a community initiative process that includes collecting feedback from communities, conducting surveys and research on issues, developing solutions, implementing programs, tracking outputs and statistics, and evaluating results. The initiative involves community members, volunteers, government, universities, and research institutes at different stages of the process from data collection to evaluation. The overall goal is to facilitate problem solving and actions that improve the community by connecting citizens and society.
Contribution to proactivity in mobile context-aware recommender systemsDaniel Gallego Vico
1) The document proposes methods for incorporating proactivity into mobile context-aware recommender systems (CARS) and evaluates their impact on user experience.
2) An architecture is presented for building social mobile CARS that integrates various social data sources while addressing privacy, cross-platform use, and cold start issues.
3) A model is described for generating proactive recommendations in mobile CARS based on assessing the appropriateness of the user's situation and suitability of item recommendations.
This document proposes a novel social media recruitment technique using machine learning. It involves extracting candidate data from social networking profiles on platforms like LinkedIn, Facebook, and Twitter. This data would then be analyzed using machine learning algorithms like logistic regression to predict the best candidates. The model aims to provide recruiters with a more holistic understanding of candidates compared to traditional recruitment methods. Case studies show this approach can reduce hiring costs and time while increasing hiring manager satisfaction. Future work would involve implementing a prototype and acquiring quality training data.
Knowledge Management in Healthcare AnalyticsGregory Nelson
The promise of actionable analytics in healthcare poses an inherent challenge as we seek to accelerate the time it takes to go from question to insight to action. The velocity of change, the demand for bigger data, the allure of advanced algorithms, the need for deeper insights, and the cost of inaction make knowledge capture and reuse an all too allusive goal.
In an evolving environment, healthcare organizations need to find ways to make greater use of prior investments in analytics products by reusing the commonalities of proven designs, metadata, business rules, captured learnings, and collaborative insights and applying them to future analytics products. By doing so in a strategic manner, they will be able to create rapid and efficient analytics processes and better manage time to value and reuse.
In this presentation, authors from two very different health systems with two very different patient populations will share their perspectives of the value of knowledge management and discuss the role of analytics in driving towards a learning health system. The authors will highlight opportunities and challenges using examples across clinical, financial, and operational domains.
This document outlines a study examining the entrepreneurial relationship development (ERD) capabilities of librarians and how those capabilities support the knowledge economy and socio-cultural changes. It provides background on the changing roles of librarians and defines key terms like knowledge economy and ERD. The study aims to understand librarians' ERD capabilities and how those capabilities enhance the knowledge economy and socio-cultural changes. Preliminary findings suggest that information behaviors and interactive practices positively influence relational capabilities, which in turn positively influence the knowledge economy and socio-cultural changes.
This presentation is by ESN's Policy Director, Alfonso Lara Montero at the Latin American Congress of Social Work in Merida, Spain on 20 October 2017. ESN has run a session on social innovation with ESN members from Belgium and Finland presenting evidence-based social services for children and families.
Presentation by the OECD on the “World Class Civil Service" made at the meeti...OECD Governance
This presentation by Edwin Lau, OECD, on the “WorLd Class Civil Service" was made at the meeting of the OECD Working Party on Public Employment and Management on 20-21 April 2015.
For further on information on the OECD work on Public Employment and Management please see http://www.oecd.org/gov/pem/.
Data Harvesting, Curation and Fusion Model to Support Public Service Recommen...Citadelh2020
CITADEL is a H2020 European project that is creating an ecosystem of best practices, tools, and recommendations to transform Public Administrations (PAs) via an inclusive approach in order to provide stakeholders with more efficient, inclusive and citizen-centric services. The CITADEL ecosystem will allow PAs to use what they already know plus new data to implement what really matters to citizens in order to shape and co-create more efficient and inclusive public services. CITADEL innovates by using ICTs to find out why citizens stop using public services, and use this information to re-adjust provision to bring them back in. Also, it identifies why citizens are not using a given public service (due to affordability, accessibility, lack of knowledge, embarrassment, lack of interest, etc.) and, where appropriate, use this information to make public services more attractive, so they start using the services.
The DataTank, a tool designed and developed by IMEC’s IDLab, will be extended to provide the Data Harvesting/Curation/Fusion (DHCF) component of the platform. The DataTank provides an open source, open data platform which not only allows publishing datasets according to standardised guidelines and taxonomies (DCAT-AP), but also transforms the data into a variety of reusable formats. The extension will include an intelligent way of harvesting and fusion of different data sources using semantics and Linked Data mapping technologies developed by IDLab. In the context of CITADEL the new HCF component will enable the visualization and analysis of trends for the usage of public services in European cities, playing a key role in generating personalized recommendations to the citizens as well as to PAs in terms of suggesting improvements to the current suite of public services.
https://twitter.com/Citadelh2020
https://twitter.com/gayane_sedraky
https://twitter.com/imec_int
https://twitter.com/IDLabResearch
Data Harvesting, Curation and Fusion Model to Support Public Service Recommen...Gayane Sedrakyan
CITADEL is a H2020 European project that is creating an ecosystem of best practices, tools, and recommendations to transform Public Administrations (PAs) via an inclusive approach in order to provide stakeholders with more efficient, inclusive and citizen-centric services. The CITADEL ecosystem will allow PAs to use what they already know plus new data to implement what really matters to citizens in order to shape and co-create more efficient and inclusive public services. CITADEL innovates by using ICTs to find out why citizens stop using public services, and use this information to re-adjust provision to bring them back in. Also, it identifies why citizens are not using a given public service (due to affordability, accessibility, lack of knowledge, embarrassment, lack of interest, etc.) and, where appropriate, use this information to make public services more attractive, so they start using the services.
The DataTank, a tool designed and developed by IMEC’s IDLab, will be extended to provide the Data Harvesting/Curation/Fusion (DHCF) component of the platform. The DataTank provides an open source, open data platform which not only allows publishing datasets according to standardised guidelines and taxonomies (DCAT-AP), but also transforms the data into a variety of reusable formats. The extension will include an intelligent way of harvesting and fusion of different data sources using semantics and Linked Data mapping technologies developed by IDLab. In the context of CITADEL the new HCF component will enable the visualization and analysis of trends for the usage of public services in European cities, playing a key role in generating personalized recommendations to the citizens as well as to PAs in terms of suggesting improvements to the current suite of public services.
Using case-based methods to assess scalability and sustainability: Lessons fr...Barb Knittel
Overview of the SC4CCM project and end-line evaluation questions focused on scalability and sustainability. Methodological approaches including case selection strategies, mixed method approaches, within-case and cross-case analysis processes. (Sangeeta Mookherji, GWU)
Skills for the new generation of statisticians Dario Buono
This presentation analyses the competence profile of official statisticians with a particular focus on new data science competences. Modernization of official statistics will depend on the capability to incorporate new data sources and benefit from “disruptive technologies”. This will require new capabilities, skills and competences that may not be part of the traditional skill set of official statisticians. The document was presented to the Conference of European Statisticians organised at the United Nation in Geneva
HOBBIT project overview presented at European Big Data Value Forum, 21-23 Nov 2017, held in Versailles, France (Palais des Congres).
This work was supported by grants from the EU H2020 Framework Programme provided for the project HOBBIT (GA no. 688227).
This document outlines a study on implementing a big data and analytics system to improve monitoring and evaluation in the state of Osun, Nigeria. The study found that while the agencies responsible for information technology support are aware of big data concepts, they currently have no business case for big data initiatives. It also revealed that the current monitoring and evaluation system is not achieving desired results and that big data resources and expertise are scarce. The study analyzed options for implementation, including outsourcing, insourcing, or a public-private partnership. It was concluded that implementing the recommendations from this study using relevant frameworks could help address Osun state's challenges in making informed decisions and improving project, program, and policy implementation.
Presentation by Tarisirai Zengeni, IIED, as part of the series of regional workshops hosted by the Resilient Andes to Climate Change Regional Project (“Andes Resilientes”), which took place from August 23 to September 13, 2022.
This document discusses the Policy Compass project, which aims to integrate open data, social media, and other tools to provide better indicators for assessing the impact of governmental policies. It identifies two scenarios for field trials: one focusing on adult education funding in Cambridgeshire, UK, and another on developing the information society in Leningrad Region, Russia. For the Russian scenario, the document outlines the regional development program, goals and metrics, and potential impact of the Policy Compass platform to increase analytical support and motivate civil servants and citizens.
Experience Strategy group at Clockwork delivered a content strategy presentation to the Content Strategy Meetup group in Minneapolis. The presentation includes a brief overview of Clockwork, and deep, in-depth view of how the strategists at Clockwork think about and do content strategy. This presentation was introduced by Laura Horan and presented by Amber James.
ASSESSMENT OF SERVICE QUALITY DELIVERY IN RURAL DISTRICT:Tryson Yangailo
This document summarizes a research presentation on assessing service quality delivery in Senanga Town Council, Zambia. The presentation covers the background, problem statement, research questions and objectives, which aim to evaluate the levels of service quality provided by the council and determine if a relationship exists between quality and customer satisfaction. Based on a survey of residents using the FM-SERVQUAL instrument, the findings show the council meets minimum standards in only one of four quality components. While technology and ICT impact satisfaction, overall there is no relationship between quality and satisfaction. Recommendations include improving staffing, adopting new technologies, and increasing government support to boost quality across components.
Facebook London - Learning from User InteractionsRishabh Mehrotra
As increasingly larger proportions of users interact with online services like search engines and recommender systems to satisfy their information needs, developing better understanding of user interactions becomes important for improving user experience and gauging user satisfaction. In this talk, I will focus on different aspects of user behavior, and present algorithms that learn from user interactions. Starting with understanding user’s information needs, I will present techniques which aim at extracting tasks from a collection of search log data. The mined knowledge from log activity data reveals users' underlying intentions and interests, which provide unique signals for human centric optimization and personalization. I will discuss different ways of building user models which leverage such behavioral signals. Going beyond user modeling, I will touch upon novel ways of leveraging user interaction sequences to detect implicit measures of user satisfaction for metric development. Finally, I will discuss offline counterfactual estimation of online metrics which are essential for efficient experimentation.
The document summarizes the community engagement efforts of a city over a three year period. It describes key milestones and approaches taken, including hiring a community engagement coordinator, establishing a core group, conducting needs assessments, and approving plans. It also evaluates the sustainability of the current coordination approach, examining how well staff conduct engagement, staff and participant experiences, and public involvement. Findings show the use of consultation, various techniques, and marketing channels. Staff expressed a desire to improve processes and involve community members earlier.
The document provides an overview of Jisc's Learning Analytics project which aims to help higher education institutions in the UK improve student retention, achievement, and employability through the application of learning analytics techniques. The project involves three core strands: a learning analytics service, toolkit, and community. It also discusses the architecture, data structures, how institutions can get involved, and provides examples of analytics activities at different universities.
This document discusses social media analytics and some of the challenges involved. It provides an overview of different types of social media analytics including sentiment analysis, social network analysis, and image/video analysis. Real-time and non-real-time customer and competitive analytics are also discussed. The document outlines some of the processes involved in social media analytics and highlights challenges like bias in social media data and unstructured social media data.
This document outlines a thesis on analyzing the role of stakeholders in managing road construction projects with Addis Ababa Roads Authority. It includes an introduction outlining the problem statement, research questions and objectives. It then describes the conceptual framework, research methods including data collection and analysis. Key findings are that different criteria are used to identify stakeholders and engagement approaches. Stakeholders play various roles in projects with clients and donors having most influence. Challenges include communication gaps and incompatible interests. Recommendations include improving communication and working closely with clients.
DELSA/GOV 3rd Health meeting - Barbara UBALDIOECD Governance
This presentation by Barbara UBALDI was made at the 3rd Joint DELSA/GOV Health Meeting, Paris 24-25 April 2014. Find out more at www.oecd.org/gov/budgeting/3rdmeetingdelsagovnetworkfiscalsustainabilityofhealthsystems2014.htm
Data Harvesting, Curation and Fusion Model to Support Public Service Recommen...Citadelh2020
CITADEL is a H2020 European project that is creating an ecosystem of best practices, tools, and recommendations to transform Public Administrations (PAs) via an inclusive approach in order to provide stakeholders with more efficient, inclusive and citizen-centric services. The CITADEL ecosystem will allow PAs to use what they already know plus new data to implement what really matters to citizens in order to shape and co-create more efficient and inclusive public services. CITADEL innovates by using ICTs to find out why citizens stop using public services, and use this information to re-adjust provision to bring them back in. Also, it identifies why citizens are not using a given public service (due to affordability, accessibility, lack of knowledge, embarrassment, lack of interest, etc.) and, where appropriate, use this information to make public services more attractive, so they start using the services.
The DataTank, a tool designed and developed by IMEC’s IDLab, will be extended to provide the Data Harvesting/Curation/Fusion (DHCF) component of the platform. The DataTank provides an open source, open data platform which not only allows publishing datasets according to standardised guidelines and taxonomies (DCAT-AP), but also transforms the data into a variety of reusable formats. The extension will include an intelligent way of harvesting and fusion of different data sources using semantics and Linked Data mapping technologies developed by IDLab. In the context of CITADEL the new HCF component will enable the visualization and analysis of trends for the usage of public services in European cities, playing a key role in generating personalized recommendations to the citizens as well as to PAs in terms of suggesting improvements to the current suite of public services.
https://twitter.com/Citadelh2020
https://twitter.com/gayane_sedraky
https://twitter.com/imec_int
https://twitter.com/IDLabResearch
Data Harvesting, Curation and Fusion Model to Support Public Service Recommen...Gayane Sedrakyan
CITADEL is a H2020 European project that is creating an ecosystem of best practices, tools, and recommendations to transform Public Administrations (PAs) via an inclusive approach in order to provide stakeholders with more efficient, inclusive and citizen-centric services. The CITADEL ecosystem will allow PAs to use what they already know plus new data to implement what really matters to citizens in order to shape and co-create more efficient and inclusive public services. CITADEL innovates by using ICTs to find out why citizens stop using public services, and use this information to re-adjust provision to bring them back in. Also, it identifies why citizens are not using a given public service (due to affordability, accessibility, lack of knowledge, embarrassment, lack of interest, etc.) and, where appropriate, use this information to make public services more attractive, so they start using the services.
The DataTank, a tool designed and developed by IMEC’s IDLab, will be extended to provide the Data Harvesting/Curation/Fusion (DHCF) component of the platform. The DataTank provides an open source, open data platform which not only allows publishing datasets according to standardised guidelines and taxonomies (DCAT-AP), but also transforms the data into a variety of reusable formats. The extension will include an intelligent way of harvesting and fusion of different data sources using semantics and Linked Data mapping technologies developed by IDLab. In the context of CITADEL the new HCF component will enable the visualization and analysis of trends for the usage of public services in European cities, playing a key role in generating personalized recommendations to the citizens as well as to PAs in terms of suggesting improvements to the current suite of public services.
Using case-based methods to assess scalability and sustainability: Lessons fr...Barb Knittel
Overview of the SC4CCM project and end-line evaluation questions focused on scalability and sustainability. Methodological approaches including case selection strategies, mixed method approaches, within-case and cross-case analysis processes. (Sangeeta Mookherji, GWU)
Skills for the new generation of statisticians Dario Buono
This presentation analyses the competence profile of official statisticians with a particular focus on new data science competences. Modernization of official statistics will depend on the capability to incorporate new data sources and benefit from “disruptive technologies”. This will require new capabilities, skills and competences that may not be part of the traditional skill set of official statisticians. The document was presented to the Conference of European Statisticians organised at the United Nation in Geneva
HOBBIT project overview presented at European Big Data Value Forum, 21-23 Nov 2017, held in Versailles, France (Palais des Congres).
This work was supported by grants from the EU H2020 Framework Programme provided for the project HOBBIT (GA no. 688227).
This document outlines a study on implementing a big data and analytics system to improve monitoring and evaluation in the state of Osun, Nigeria. The study found that while the agencies responsible for information technology support are aware of big data concepts, they currently have no business case for big data initiatives. It also revealed that the current monitoring and evaluation system is not achieving desired results and that big data resources and expertise are scarce. The study analyzed options for implementation, including outsourcing, insourcing, or a public-private partnership. It was concluded that implementing the recommendations from this study using relevant frameworks could help address Osun state's challenges in making informed decisions and improving project, program, and policy implementation.
Presentation by Tarisirai Zengeni, IIED, as part of the series of regional workshops hosted by the Resilient Andes to Climate Change Regional Project (“Andes Resilientes”), which took place from August 23 to September 13, 2022.
This document discusses the Policy Compass project, which aims to integrate open data, social media, and other tools to provide better indicators for assessing the impact of governmental policies. It identifies two scenarios for field trials: one focusing on adult education funding in Cambridgeshire, UK, and another on developing the information society in Leningrad Region, Russia. For the Russian scenario, the document outlines the regional development program, goals and metrics, and potential impact of the Policy Compass platform to increase analytical support and motivate civil servants and citizens.
Experience Strategy group at Clockwork delivered a content strategy presentation to the Content Strategy Meetup group in Minneapolis. The presentation includes a brief overview of Clockwork, and deep, in-depth view of how the strategists at Clockwork think about and do content strategy. This presentation was introduced by Laura Horan and presented by Amber James.
ASSESSMENT OF SERVICE QUALITY DELIVERY IN RURAL DISTRICT:Tryson Yangailo
This document summarizes a research presentation on assessing service quality delivery in Senanga Town Council, Zambia. The presentation covers the background, problem statement, research questions and objectives, which aim to evaluate the levels of service quality provided by the council and determine if a relationship exists between quality and customer satisfaction. Based on a survey of residents using the FM-SERVQUAL instrument, the findings show the council meets minimum standards in only one of four quality components. While technology and ICT impact satisfaction, overall there is no relationship between quality and satisfaction. Recommendations include improving staffing, adopting new technologies, and increasing government support to boost quality across components.
Facebook London - Learning from User InteractionsRishabh Mehrotra
As increasingly larger proportions of users interact with online services like search engines and recommender systems to satisfy their information needs, developing better understanding of user interactions becomes important for improving user experience and gauging user satisfaction. In this talk, I will focus on different aspects of user behavior, and present algorithms that learn from user interactions. Starting with understanding user’s information needs, I will present techniques which aim at extracting tasks from a collection of search log data. The mined knowledge from log activity data reveals users' underlying intentions and interests, which provide unique signals for human centric optimization and personalization. I will discuss different ways of building user models which leverage such behavioral signals. Going beyond user modeling, I will touch upon novel ways of leveraging user interaction sequences to detect implicit measures of user satisfaction for metric development. Finally, I will discuss offline counterfactual estimation of online metrics which are essential for efficient experimentation.
The document summarizes the community engagement efforts of a city over a three year period. It describes key milestones and approaches taken, including hiring a community engagement coordinator, establishing a core group, conducting needs assessments, and approving plans. It also evaluates the sustainability of the current coordination approach, examining how well staff conduct engagement, staff and participant experiences, and public involvement. Findings show the use of consultation, various techniques, and marketing channels. Staff expressed a desire to improve processes and involve community members earlier.
The document provides an overview of Jisc's Learning Analytics project which aims to help higher education institutions in the UK improve student retention, achievement, and employability through the application of learning analytics techniques. The project involves three core strands: a learning analytics service, toolkit, and community. It also discusses the architecture, data structures, how institutions can get involved, and provides examples of analytics activities at different universities.
This document discusses social media analytics and some of the challenges involved. It provides an overview of different types of social media analytics including sentiment analysis, social network analysis, and image/video analysis. Real-time and non-real-time customer and competitive analytics are also discussed. The document outlines some of the processes involved in social media analytics and highlights challenges like bias in social media data and unstructured social media data.
This document outlines a thesis on analyzing the role of stakeholders in managing road construction projects with Addis Ababa Roads Authority. It includes an introduction outlining the problem statement, research questions and objectives. It then describes the conceptual framework, research methods including data collection and analysis. Key findings are that different criteria are used to identify stakeholders and engagement approaches. Stakeholders play various roles in projects with clients and donors having most influence. Challenges include communication gaps and incompatible interests. Recommendations include improving communication and working closely with clients.
DELSA/GOV 3rd Health meeting - Barbara UBALDIOECD Governance
This presentation by Barbara UBALDI was made at the 3rd Joint DELSA/GOV Health Meeting, Paris 24-25 April 2014. Find out more at www.oecd.org/gov/budgeting/3rdmeetingdelsagovnetworkfiscalsustainabilityofhealthsystems2014.htm
Similar to Social Service Policy Evaluation Using High-Fidelity Client Emulation (20)
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of May 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Build applications with generative AI on Google CloudMárton Kodok
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
Enhanced data collection methods can help uncover the true extent of child abuse and neglect. This includes Integrated Data Systems from various sources (e.g., schools, healthcare providers, social services) to identify patterns and potential cases of abuse and neglect.
4. Problem Definition
08-28-2017 Social Service Policy Evaluation Using Client Emulation 4
Why focus on the homeless?
• Canada 2016
• 35,000 homeless Canadians on any given night
• (+17.5% from 2014)
• 27% women, 19% youth, 24% aged 50+
• India 2011
• 1% estimated homeless in cities
• Mumbai: 200,000 (including Navi Mumbai)
• Delhi: 150,000 - 200,000
• Kolkata: 150,000
• Ahmedabad: 100,000
• Hyderabad: 60,000
• USA 2015
• 576,450 homeless Americans on any given night
• (-2% from 2014)
• Varies greatly from state to state.
• Requires tailored, client-centric policy.
http://endhomelessness.org
http://homelesshub.ca/SOHC2016
http://hlrn.org.in/homelessness
5. Problem Definition: Policy Evaluation
• Key Insights about the homeless population:
• Often seen through the filter of social norms.
• Face different limitations than the rest of the population in their society, and live by different
social norms.
• Life choices seem irrational, incompatible with society, and detrimental to their own
wellbeing.
• Traditionally:
• Large scale simulations try to close the gap between program trials and implementation.
• Probabilistic models are based on decisions made under past policies.
• Social Science models rely on social norms and structural factors.
• Limitations:
• Need to know how clients will react in the future under new policies, not past policies.
• Social science models are not always applicable due to different social norms.
• High-fidelity agent:
• Capable of emulating seemingly “irrational” behaviour.
08-28-2017 Social Service Policy Evaluation Using Client Emulation 5
6. Background
• What are the models of decision making?
1. Rational view according to decision theory is based on an objective
understanding of choices.
• Economists and AI focus on understanding the process of decision-making (Etzioni,
1988; Russell, 1997).
• Any factors that impact utility maximization.
2. Behavioural view is based on a subjective understanding of choices.
• Psychologists and sociologists focus on the interpretation of observed behaviour
(Simon, 1967; Simon, 1996; Klymchuk, 2014; Etzioni, 1988).
• Any factor that can explain the observed behaviour.
08-28-2017 Social Service Policy Evaluation Using Client Emulation 6
7. Approach
• Merged view of decision making [Gajderowicz, 2017a]:
1. Begin with the reasoning view.
• AI planner to emulate client choices.
2. Extend reasoning view with factors that change utility ( ∆U ) of different
actions.
• ∆U : Basic human needs and emotional states.
3. Incorporate the behavioral view:
• Calibrate the model using data about client decisions from a pilot
study.
08-28-2017 Social Service Policy Evaluation Using Client Emulation 7
8. Scenario: “John”
• Imagine John who meets with a social worker.
• John wants to exit homelessness, but has had a hard time finding a
place that meet his needs:
• Close to favourite soup kitchen.
• In neighbourhood to existing shelter.
• Close to community centre to visit friends.
• Close to store to make minor purchases.
• On the 2nd or 3rd floor.
• Must face east.
• The social worker sets out a plan for John:
1. Move into an apartment that is available.
2. Apartment is on the 2nd floor but faces north.
3. Close to his friends, but not the soup kitchen.
4. Food can be delivered in the first month.
5. After one month John can get a food stipend and go to a local grocery store.
08-28-2017 Social Service Policy Evaluation Using Client Emulation 8
9. Rational Reasoning
08-28-2017
sh
st
sk
cc
st
sh
cc
st
sh
sk
sk
sh
cc
st
cc
st
st
sh
st
sk
cc
. . . cc
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
sh
sh
cc
sh
sh
cc
sh
sh
. . . sk
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
• starting state “at shelter” and
• services believed to satisfy goals:
“state => goal(s)”
food
friends clothing
+ food
start at
shelter
end at
home
Agent Beliefs
sh => security + home
sk => food
cc => friends
st => clothing + food
Initial state ( S ):
at shelter (sh)
Social Service Policy Evaluation Using Client Emulation 9
Search tree for sequencing and searching states
that satisfy an agent’s goals.
• Each state represents use of a service:
shelter (sh), soup kitchen (sk),
community centre (cc), or store (st)
• Blue state is part of client’s chosen path.
• Green state is part of SW’s path.
U 3
U 4
U 6
U 5 Goals ( G ):
- food
- security
- friends
- clothing
- end at home
max U P : G
U 2
U 1
10. Bounded Rational Reasoning
08-28-2017
I bound : missing or wrong information
e.g. food not available in soup kitchen, only
at store and community centre.
sh
st
sk
cc
st
sh
cc
st
sh
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friends
+ food
Social Service Policy Evaluation Using Client Emulation 10
max U P : G
U 2
U 4
Result: Prune branches that don’t
match known information.
Adjust utility of remaining
paths.
Exclude correct plans with
soup kitchen.
U 3
U 1
14. Approach
• Emotions ???
• Appraisal theory, arousal theory, etc: need to know before hand.
• Expectation of success where |G S | = total satisfied goals and |G| = all goals.
• Example: expectation of success when goals do not change (left) or goals increase
over time (right).
• Neither captures expectation change describes in behaviour psychology literature.
Expectation of Success
|G S |
Expectation without
goal growth
08-28-2017 Social Service Policy Evaluation Using Client Emulation 14
|G|0
100%
Expectation of Success
|G S |
Expectation with initially
exponential goal growth
|G|0
100%
|G S |
|G |
15. Approach
08-28-2017 Social Service Policy Evaluation Using Client Emulation 15
• Emotional Cycle of Change (ECOC)
• Behavior change according to ECOC theory (Kelly, 1979).
• ECOC defines how expectation of success changes when information about goals
becomes available.
• Below emotional thresholds, goals are removed and reordered (∆G) as expectations
change (Gajderowicz, 2017b).
Mood
Time
Emotional Cycle of Change (ECOC)
1) Uninformed Optimism
2) Informed
Pessimism
3) Valley of Despair
4) Hopeful Realism
5) Informed Optimism
6) Success
100%
|G S |
|G |
( )P(E) = ecoc
P(E)
19. Experiment 1.1 (RNN) Design
When can you predict client success in intervention program?
• Objective:
• Evaluate predictive power of changing client needs (∆G) and demographics.
• Hypothesis:
• Client need transitions plus demographics can be used to predictive client status at end of
study.
• Method:
• Recurrent Neural Network (RNN) is used to predict client outcomes in an intervention
program with temporal (time-series) data.
• Based on total needs per MH level.
• Dependent Variable:
• Missing, success or failure in the program.
• Independent Variables:
• Client demographics: top-11 as per p–value and key demographics.
• Client need trajectories (∆G) mapped to Maslow’s Hierarchy.
08-28-2017 Social Service Policy Evaluation Using Client Emulation 19
20. 08-28-2017 20
RNN prediction score is accuracy (y-axis):
Analysis
• Increase in accuracy from 3 to 6 months.
• Higher standard deviation for mean of needs at 6
months.
• Individual demographics have good predictive power
(>= 0.75) after 6 months.
• Best demographics:
o Attended Mental Facility,
o Relatively homeless,
o Attended Health Facility,
o Employment Status,
o Duration of Unemployment.
Social Service Policy Evaluation Using Client Emulation
Experiment 1.1 Results
Prediction Score =
TP + TN
P + N
Conclusion
• Hypothesis is proven true: By considering certain demographics and changes in MH needs, it is
possible to predict client outcome in the HF intervention program.
• Changing MH needs (∆G) are a valid predictive measure.
21. Experiment 1.2 (SVM) Design
Predict client success in intervention program.
• Objective:
• Evaluate predictive power of client needs and emotional state against existing methods.
• Hypothesis:
• Client needs and ECOC stages have equal or better predictive power than currently used
methods that rely on client demographics at intake.
• Method:
• Support vector machine (SVM) is used to predict client outcomes in an intervention program.
• Based on total needs per MH level and ECOC state machine.
• Dependent Variable:
• Success or failure in the program.
• Independent Variables:
• Client demographics: all; mental health, top-2 (employment and mental facility); and key-3
(age, mental health, absolutely/relatively homeless).
• Client need trajectories mapped to Maslow’s Hierarchy (omitting self-actualization).
• ECOC state machine and calibrated weights.
08-28-2017 Social Service Policy Evaluation Using Client Emulation 21
22. ML Counts Only
Best with
Demographics
ECOC +
Mental Issues
Configuration
Top Demographics, MH, and ECOC Stages
08-28-2017 22
SVM prediction score is accuracy (y-axis):
Analysis
• Demographics (“demo”)
o top-2 demographics had 0.69 accuracy
• Maslow’s Hierarchy of Needs
o Without demographics, MH needs had 0.67 accuracy.
o Adding demographics improved the accuracy to 0.72.
• Simulated ECOC stages with state machine and calibrated
weights.
o ECOC levels only had small improvement in accuracy.
Weighted score with Mental Health had best accuracy at
0.76
Social Service Policy Evaluation Using Client Emulation
Experiment 1.2 Results
Prediction Score =
TP + TN
P + N
Conclusion
• Just relying on ML counts gives good predictions compared to demographics.
• Simulated ECOC stages with calibrated weights give 9% improvement.
25. Experiment 2 Results
08-28-2017 Social Service Policy Evaluation Using Client Emulation 25
• Analysis:
• Overall metric rating.
• P (sM | F, d) and P (F | sM, d) are the best metrics for
assigning models M to specific demographics.
• Top rated metrics by demographic.
• Based on these results, the best metric with highest mean
probability is P(sM|F,d) with 0.905.
• This means that there is a 90.1% probability of finding a
good model for a given demographic that exits the
program at month F.
Demographics
• Conclusion:
• We reject the null hypothesis and say that Taken Period and model score have an effect on
model score.
• We can say that these is a relationship between Taken Period, client demographics and the
emulated (∆G).