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DP-100 Designing and Implementing a Data Science Solution on Azure

Set up an Azure Machine Learning workspace (30-35%)
Create an Azure Machine Learning workspace
• create an Azure Machine Learning workspace
• configure workspace settings
• manage a workspace by using Azure Machine Learning Studio
Manage data objects in an Azure Machine Learning workspace
• register and maintain data stores
• create and manage datasets
Manage experiment compute contexts
• create a compute instance
• determine appropriate compute specifications for a training workload
• create compute targets for experiments and training

Run experiments and train models (25-30%)
Create models by using Azure Machine Learning Designer
• create a training pipeline by using Designer
• ingest data in a Designer pipeline
• use Designer modules to define a pipeline data flow
• use custom code modules in Designer
Run training scripts in an Azure Machine Learning workspace
• create and run an experiment by using the Azure Machine Learning SDK
• consume data from a data store in an experiment by using the Azure Machine Learning
SDK
• consume data from a dataset in an experiment by using the Azure Machine Learning
SDK
• choose an estimator
Generate metrics from an experiment run
• log metrics from an experiment run
• retrieve and view experiment outputs
• use logs to troubleshoot experiment run errors
Automate the model training process
• create a pipeline by using the SDK
• pass data between steps in a pipeline
• run a pipeline
• monitor pipeline runs

Optimize and manage models (20-25%)
Use Automated ML to create optimal models
• use the Automated ML interface in Studio
• use Automated ML from the Azure ML SDK
• select scaling functions and pre-processing options
• determine algorithms to be searched
• define a primary metric
• get data for an Automated ML run
• retrieve the best model
Use Hyperdrive to rune hyperparameters
• select a sampling method
• define the search space
• define the primary metric
• define early termination options
• find the model that has optimal hyperparameter values
Use model explainers to interpret models
• select a model interpreter
• generate feature importance data
Manage models
• register a trained model
• monitor model history
• monitor data drift

Deploy and consume models (20-25%)
Create production compute targets
• consider security for deployed services
• evaluate compute options for deployment
Deploy a model as a service
• configure deployment settings
• consume a deployed service
• troubleshoot deployment container issues
Create a pipeline for batch inferencing
• publish a batch inferencing pipeline
• run a batch inferencing pipeline and obtain outputs
Publish a Designer pipeline as a web service
• create a target compute resource
• configure an Inference pipeline
• consume a deployed endpoint

Set up an Azure Machine Learning workspace (30-35%)
Create an Azure Machine Learning workspace
• create an Azure Machine Learning workspace
• configure workspace settings
• manage a workspace by using Azure Machine Learning sStudio
Manage data objects in an Azure Machine Learning workspace
• register and maintain data stores
• create and manage datasets
Manage experiment compute contexts
• create a compute instance
• determine appropriate compute specifications for a training workload
• create compute targets for experiments and training

Run experiments and train models (25-30%)
Create models by using Azure Machine Learning Designer
• create a training pipeline by using Azure Machine Learning Ddesigner
• ingest data in a Designer designer pipeline
• use Designer designer modules to define a pipeline data flow
• use custom code modules in Designer designer
Run training scripts in an Azure Machine Learning workspace
• create and run an experiment by using the Azure Machine Learning SDK
• consume data from a data store in an experiment by using the Azure Machine Learning
SDK
• consume data from a dataset in an experiment by using the Azure Machine Learning
SDK
• choose an estimator for a training experiment
Generate metrics from an experiment run
• log metrics from an experiment run
• retrieve and view experiment outputs
• use logs to troubleshoot experiment run errors
Automate the model training process
• create a pipeline by using the SDK
• pass data between steps in a pipeline
• run a pipeline
• monitor pipeline runs

Optimize and manage models (20-25%)
Use Automated ML to create optimal models
• use the Automated ML interface in Azure Machine Learning Studiostudio
• use Automated ML from the Azure Machine Learning SDK
• select scaling functions and pre-processing options
• determine algorithms to be searched
• define a primary metric
• get data for an Automated ML run
• retrieve the best model
Use Hyperdrive to rune tune hyperparameters
• select a sampling method
• define the search space
• define the primary metric
• define early termination options
• find the model that has optimal hyperparameter values
Use model explainers to interpret models
• select a model interpreter
• generate feature importance data
Manage models
• register a trained model
• monitor model history
• monitor data drift

Deploy and consume models (20-25%)
Create production compute targets
• consider security for deployed services
• evaluate compute options for deployment
Deploy a model as a service
• configure deployment settings
• consume a deployed service
• troubleshoot deployment container issues
Create a pipeline for batch inferencing
• publish a batch inferencing pipeline
• run a batch inferencing pipeline and obtain outputs
Publish a Designer designer pipeline as a web service
• create a target compute resource
• configure an Inference pipeline
• consume a deployed endpoint

Designing and Implementing a Data Science Solution on Azure
Microsoft Implementing information hunger

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Microsoft
DP-100
Designing and Implementing a Data Science Solution
on Azure
http://killexams.com/pass4sure/exam-detail/DP-100
Question: 98
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains
a unique solution that might meet the stated goals. Some question sets might have more than one correct solution,
while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not
appear in the review screen.
You are analyzing a numerical dataset which contain missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature
set.
You need to analyze a full dataset to include all values.
Solution: Use the last Observation Carried Forward (IOCF) method to impute the missing data points.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Instead use the Multiple Imputation by Chained Equations (MICE) method.
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method
described in the statistical literature as "Multivariate Imputation using Chained Equations" or "Multiple Imputation by
Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally
using the other variables in the data before filling in the missing values.
Note: Last observation carried forward (LOCF) is a method of imputing missing data in longitudinal studies. If a
person drops out of a study before it ends, then his or her last observed score on the dependent variable is used for all
subsequent (i.e., missing) observation points. LOCF is used to maintain the demo size and to reduce the bias caused
by the attrition of participants in a study.
References:
https://methods.sagepub.com/reference/encyc-of-research-design/n211.xml
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/
Question: 99
You deploy a real-time inference service for a trained model.
The deployed model supports a business-critical application, and it is important to be able to monitor the data
submitted to the web service and the predictions the data generates.
You need to implement a monitoring solution for the deployed model using minimal administrative effort.
What should you do?
A. View the explanations for the registered model in Azure ML studio.
B. Enable Azure Application Insights for the service endpoint and view logged data in the Azure portal.
C. Create an ML Flow tracking URI that references the endpoint, and view the data logged by ML Flow.
D. View the log files generated by the experiment used to train the model.
Answer: B
Explanation:
Configure logging with Azure Machine Learning studio
You can also enable Azure Application Insights from Azure Machine Learning studio. When you�re ready to deploy
your model as a web service, use the following steps to enable Application Insights:
Question: 100
You are solving a classification task.
You must evaluate your model on a limited data demo by using k-fold cross validation. You start by
configuring a k parameter as the number of splits.
You need to configure the k parameter for the cross-validation.
Which value should you use?
A. k=0.5
B. k=0
C. k=5
D. k=1
Answer: C
Explanation:
Leave One Out (LOO) cross-validation
Setting K = n (the number of observations) yields n-fold and is called leave-one out cross-validation (LOO), a special
case of the K-fold approach.
LOO CV is sometimes useful but typically doesn�t shake up the data enough. The estimates from each fold are highly
correlated and hence their average can have high variance.
This is why the usual choice is K=5 or 10. It provides a good compromise for the bias-variance tradeoff.
Question: 101
DRAG DROP
You create an Azure Machine Learning workspace.
You must implement dedicated compute for model training in the workspace by using Azure Synapse compute
resources. The solution must attach the dedicated compute and start an Azure Synapse session.
You need to implement the compute resources.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions
to the answer area and arrange them in the correct order.
Answer:
Explanation:
Question: 102
You deploy a real-time inference service for a trained model.
The deployed model supports a business-critical application, and it is important to be able to monitor the data
submitted to the web service and the predictions the data generates.
You need to implement a monitoring solution for the deployed model using minimal administrative effort.
What should you do?
A. View the explanations for the registered model in Azure ML studio.
B. Enable Azure Application Insights for the service endpoint and view logged data in the Azure portal.
C. Create an ML Flow tracking URI that references the endpoint, and view the data logged by ML Flow.
D. View the log files generated by the experiment used to train the model.
Answer: B
Explanation:
Configure logging with Azure Machine Learning studio
You can also enable Azure Application Insights from Azure Machine Learning studio. When you�re ready to deploy
your model as a web service, use the following steps to enable Application Insights:
Question: 103
You train a model and register it in your Azure Machine Learning workspace. You are ready to deploy the model as a
real-time web service.
You deploy the model to an Azure Kubernetes Service (AKS) inference cluster, but the deployment fails because an
error occurs when the service runs the entry script that is associated with the model deployment.
You need to debug the error by iteratively modifying the code and reloading the service, without requiring a re-
deployment of the service for each code update.
What should you do?
A. Register a new version of the model and update the entry script to load the new version of the model from its
registered path.
B. Modify the AKS service deployment configuration to enable application insights and re-deploy to AKS.
C. Create an Azure Container Instances (ACI) web service deployment configuration and deploy the model on ACI.
D. Add a breakpoint to the first line of the entry script and redeploy the service to AKS.
E. Create a local web service deployment configuration and deploy the model to a local Docker container.
Answer: C
Explanation:
How to work around or solve common Docker deployment errors with Azure Container Instances (ACI) and Azure
Kubernetes Service (AKS) using Azure Machine Learning.
The recommended and the most up to date approach for model deployment is via the Model.deploy() API using an
Environment object as an input parameter. In this case our service will create a base docker image for you during
deployment stage and mount the required models all in one call.
The basic deployment tasks are:
Question: 104
HOTSPOT
You plan to implement a two-step pipeline by using the Azure Machine Learning SDK for Python.
The pipeline will pass temporary data from the first step to the second step.
You need to identify the class and the corresponding method that should be used in the second step to access
temporary data generated by the first step in the pipeline.
Which class and method should you identify? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point
Answer:
Question: 105
HOTSPOT
You are using Azure Machine Learning to train machine learning models. You need a compute target on which to
remotely run the training script.
You run the following Python code:
Answer:
Explanation:
Box 1: Yes
The compute is created within your workspace region as a resource that can be shared with other users.
Box 2: Yes
It is displayed as a compute cluster.
View compute targets
Question: 106
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains
a unique solution that might meet the stated goals. Some question sets might have more than one correct solution,
while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not
appear in the review screen.
You train a classification model by using a logistic regression algorithm.
You must be able to explain the model�s predictions by calculating the importance of each feature, both as an overall
global relative importance value and as a measure of local importance for a specific set of predictions.
You need to create an explainer that you can use to retrieve the required global and local feature importance values.
Solution: Create a TabularExplainer.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Instead use Permutation Feature Importance Explainer (PFI).
Note 1:
Note 2: Permutation Feature Importance Explainer (PFI): Permutation Feature Importance is a technique used to
explain classification and regression models. At a high level, the way it works is by randomly shuffling data one
feature at a time for the entire dataset and calculating how much the performance metric of interest changes. The larger
the change, the more important that feature is. PFI can explain the overall behavior of any underlying model but does
not explain individual predictions.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-interpretability
Question: 107
You are solving a classification task.
The dataset is imbalanced.
You need to select an Azure Machine Learning Studio module to Improve the classification accuracy.
Which module should you use?
A. Fisher Linear Discriminant Analysis.
B. Filter Based Feature Selection
C. Synthetic Minority Oversampling Technique (SMOTE)
D. Permutation Feature Importance
Answer: C
Explanation:
Use the SMOTE module in Azure Machine Learning Studio (classic) to increase the number of underepresented cases
in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply
duplicating existing cases.
You connect the SMOTE module to a dataset that is imbalanced. There are many reasons why a dataset might be
imbalanced: the category you are targeting might be very rare in the population, or the data might simply be difficult
to collect. Typically, you use SMOTE when the class you want to analyze is under-represented.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote
Question: 108
You use the following code to define the steps for a pipeline:
from azureml.core import Workspace, Experiment, Run
from azureml.pipeline.core import Pipeline
from azureml.pipeline.steps import PythonScriptStep
ws = Workspace.from_config()
. . .
step1 = PythonScriptStep(name="step1", �)
step2 = PythonScriptsStep(name="step2", �)
pipeline_steps = [step1, step2]
You need to add code to run the steps.
Which two code segments can you use to achieve this goal? Each correct answer presents a complete solution. NOTE:
Each correct selection is worth one point.
A. experiment = Experiment(workspace=ws,
name=�pipeline-experiment�)
run = experiment.submit(config=pipeline_steps)
B. run = Run(pipeline_steps)
C. pipeline = Pipeline(workspace=ws, steps=pipeline_steps) experiment = Experiment(workspace=ws, name=�pipeline-
experiment�) run = experiment.submit(pipeline)
D. pipeline = Pipeline(workspace=ws, steps=pipeline_steps)
run = pipeline.submit(experiment_name=�pipeline-experiment�)
Answer: C,D
Explanation:
After you define your steps, you build the pipeline by using some or all of those steps.
# Build the pipeline. Example:
pipeline1 = Pipeline(workspace=ws, steps=[compare_models])
# Submit the pipeline to be run
pipeline_run1 = Experiment(ws, �Compare_Models_Exp�).submit(pipeline1)
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-machine-learning-pipelines
Question: 109
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains
a unique solution that might meet the stated goals. Some question sets might have more than one correct solution,
while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not
appear in the review screen.
You create an Azure Machine Learning service datastore in a workspace.
The datastore contains the following files:
� /data/2018/Q1.csv
� /data/2018/Q2.csv
� /data/2018/Q3.csv
� /data/2018/Q4.csv
� /data/2019/Q1.csv
All files store data in the following format:
id,f1,f2i
1,1.2,0
2,1,1,
1 3,2.1,0
You run the following code:
You need to create a dataset named training_data and load the data from all files into a single data frame by using the
following code:
Solution: Run the following code:
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Use two file paths.
Use Dataset.Tabular_from_delimeted, instead of Dataset.File.from_files as the data isn�t cleansed.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-register-datasets
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Microsoft Implementing information hunger - BingNews https://killexams.com/pass4sure/exam-detail/DP-100 Search results Microsoft Implementing information hunger - BingNews https://killexams.com/pass4sure/exam-detail/DP-100 https://killexams.com/exam_list/Microsoft MICROSOFT OFFICE.EXE Information

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This file has been identified as a program that is undesirable to have running on your computer. This consists of programs that are misleading, harmful, or undesirable.

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Name

system
Filename

Microsoft Office.exe
Command

C:\Windows\System32\Microsoft Office.exe
Description
File Location

%System%
Startup Type

This startup entry is started automatically from a Run, RunOnce, RunServices, or RunServicesOnce entry in the registry.
HijackThis Category
Note

%System% is a variable that refers to the Windows System folder. By default this is C:\Windows\System for Windows 95/98/ME, C:\Winnt\System32 for Windows NT/2000, or C:\Windows\System32 for Windows XP/Vista/7.
This entry has been requested 16,803 times.

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Tue, 21 Feb 2023 21:12:00 -0600 en-us text/html https://www.bleepingcomputer.com/startups/13745/Microsoft_Office.exe/ MICROSOFT SEND.EXE Information

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If the description states that it is a piece of malware, you should immediately run an antivirus and antispyware program. If that does not help, feel free to ask us for assistance in the forums.
Name

Microsoft Send
Filename

Microsoft Send.exe
Command

C:\Windows\System32\Microsoft Send.exe
Description
File Location

%System%
Startup Type

This startup entry is installed as a Windows service.
Service Name

Microsoft Send
Display Name

Microsoft Send
HijackThis Category
Note

%System% is a variable that refers to the Windows System folder. By default this is C:\Windows\System for Windows 95/98/ME, C:\Winnt\System32 for Windows NT/2000, or C:\Windows\System32 for Windows XP/Vista/7.
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Fri, 10 Mar 2023 07:34:00 -0600 en-us text/html https://www.bleepingcomputer.com/startups/16532/Microsoft_Send.exe/ Can Big Organizations Be Agile?

Can big firms be entrepreneurial? Some speakers at last week’s Drucker Forum in Vienna Austria spent time talking about what firms could be doing, or should be doing to operate entrepreneurially. The panel in our session at the Forum spent most of our time discussing what some big firms are already doing. Our hypothesis was that the future is already here: it’s just very unevenly distributed. This two-part article is a deep dive into what we learned.

The panel began with the findings of the site visits by the SD Learning Consortium (SDLC) in 2016 to some large organizations that are implementing Agile and operating entrepreneurially at scale, including Barclays, Cerner, C.H.Robinson, Ericsson, Microsoft, Riot Games and Spotify. (The full report of the SDLC is available here.) The panel included Joakim Sundén (Spotify), Vanessa Adams (C.H.Robinson), Gary Hamel (Management Innovation eXchange) and myself.

The second part of this article will cover the fascinating discussion that ensued with Gary Hamel and the panel.

Some Examples Of Agile At Scale

Steve Denning: Some speakers at the Drucker Forum have been skeptical as to whether it is even possible for big firms to act entrepreneurially or become Agile. In a way, they are like those people who for thousands of years were convinced that all swans are white: a black swan was a contradiction in terms. Even when they learned that black swans did exist in the Antipodes, it took some time for them to accept that fact.

I’ll begin with a couple of examples of black swans that we encountered during the site visits over the past year.

The first is Ericsson—(a 140-year old Swedish firm with around 100,000 employees. Among many other things, it manages networks for the world’s telecommunications companies, covering 40% of the world’s mobile phone traffic. In 2011, this unit in Ericsson with several thousand people embraced Agile. Before 2011, Ericsson would build its systems on a five-year cycle, with a unit housing several thousand employees. When the system was finally built, it would be shipped to the telecoms and there would be an extended period of adjustment as the system was adapted to fit their needs. Now with Agile management, Ericsson has over 100 small teams working with its customers’ needs in three-week cycles. The result is faster development that is more relevant to the specific needs of the customers. The client gets value sooner. Ericsson has less work in progress. And Ericsson is deploying one to two years earlier than it otherwise would, so that its revenue comes in one to two years earlier.

The second example is Spotify a rapidly growing, 8-year old music streaming company with more than 2,500 staff and more than 100 million active users globally. In 2015, a small team in Spotify had an idea to solve a long-standing problem: how could users find the music they would really love in a library of millions of songs? What if, they asked, they could completely remove the friction for you as a user by using an algorithm to match your tastes with the several billion playlists created by other users and deliver a fresh playlist to you weekly? The team didn’t need a whole lot of ROI analyses or go up a steep hierarchical chain to get management approval to change the firm’s strategic plan. In an Agile setting, it was quick and easy for the team to carry out a series of tests. When the innovation, now known as Discover Weekly, was deployed just a few months later, it was a wild success—becoming not just a new feature but a global brand, resulting in an influx of millions of new users. The Discover Weekly team is just one of more than 100 small teams at Spotify, which has deployed Agile approaches to all work since its inception in 2008.

Barclays is a 326-year-old transatlantic bank with around 130,000 employees. In 2015, Barclays announced that embracing Agile was a key strategic initiative and encouraged hundreds of teams to become champions of an Agile transformation. There are now more than 800 teams that are part of an organization-wide Agile transformation that is aimed at enabling Barclays to deliver instant, frictionless, intimate value at scale.

Microsoft is a 41-year organization, parts of which implementing Agile and Lean. Earlier in the Drucker Forum, Gary Hamel mentioned the complaints of Microsoft’s own employees that emerged in 2007 when Windows Vista was offered to the public. In 2007, Microsoft was releasing Windows in three-year cycles with little possibility of feedback from users. Today, the situation is very different. Since 2014, Microsoft Windows10 has gone through a remarkable transformation. It is now getting feedback from an active user group of more than 7 million users and is issuing updates weekly—a game-changing acceleration. Quite apart from customers: when staff see their ideas implemented within days instead of years, it has a huge benefit for staff morale. Other parts of Microsoft such as the Developer Division and Skype are also implementing Agile.

These examples, which were identified in the 2016 site visits of the SD Learning Consortium (SDLC), are not isolated experiments in those firms. In each case, they are part of large-scale implementations of an entrepreneurial approach to running the organization with continuous innovation.

The SDLC members range in age from 8 years to 326 years. The firms, or large units within these firms, operate globally and have been on their journeys mostly for five years or more. Some of the firms were “born Agile” while others are engaged in transformation from top-down bureaucracy. Some of the firms are in fast-growing sectors like e-sports or music streaming, while others are in mature sectors like banking.

Each of the site visits included more than ten people observing what each company has done and then exploring in greater depth the issues that were uncovered. After the visits, the member firms got together for several days to review what had been learned and identify common themes. Those common themes and findings are reflected in full report available here. Each firm is sharing what is learned within its own organization in order to spur enhanced implementation of entrepreneurial goals, principles and practices on a continuous journey of discovery.

The Best-Kept Management Secret On The Planet

In some ways, Agile may be the best-kept management secret on the planet. It has been under way for over fifteen years. There are now hundreds of thousands of Agile practitioners around the world and tens of thousands of organizations implementing Agile. Yet many general managers know little about it.

One reason for that is that Agile movement got going in software development in 2001—an unexpected place for management innovation. The neglect of Agile is now changing as Agile is being embraced by all parts, and all kinds, of organizations, as noted in the Harvard Business Review article in April 2016, “Embracing Agile,.” which said:

“Now agile methodologies—which involve new values, principles, practices, and benefits and are a radical alternative to command-and-control-style management—are spreading across a broad range of industries and functions and even into the C-suite.”

The Agile movement is driven both by the passion of those who love working this way and by managers who recognize that survival in an unpredictable and rapidly shifting marketplace requires a capacity to adapt equally rapidly.

The Four Main Themes Of Agile

Although the SDLC site visits revealed many variations in managerial practices, and different labels applied to what was being done, SDLC members noted a striking convergence around four themes:

• Delighting customers: An obsession with continuously adding value for customers and users. Basically firms now have to generate instant, intimate, frictionless value at scale, anywhere, anytime, on any device. This is more than an increased attention to customers: it is a shift in the goal of the organization—a veritable Copernican revolution in management.

• Descaling work: A presumption that in a volatile, complex, uncertain and ambiguous world, big difficult problems need to be disaggregated into small batches and performed by small cross-functional autonomous teams, working iteratively in short cycles in a state of flow, with fast feedback from customers and end-users.

• Enterprise-wide Agility: A recognition that, to be fully entrepreneurial, the whole organization needs to embrace the entrepreneurial mindset so that the entire firm functions increasingly as an interactive network. Agile is not just for IT: it is a change in the way that the whole organization thinks, is led and managed.

• Nurturing culture: A never-ending commitment to actively nurture, and systematically strengthen, entrepreneurial mindsets and behavior throughout the organization.

The SDLC members believe that pursuit of all four themes is key to sustaining the embrace of Agile. Individually, none of the observed management practices are new. What is new and different is the way that Agile management goals, practices and values constitute a coherent and integrated approach to continuous innovation, driven by and lubricated with a pervasive entrepreneurial mindset.

For some critics of Agile, the passion with which both managers and staff pursue an Agile approach to management is confused with zealotry or with the mistaken belief that Agile is being presented as a panacea. As you will hear in the following presentations, Agile itself not only offers many implementation challenges. It also does what bureaucracy never even attempted: it mobilizes people’s energy and enthusiasm and generates meaning both at work and in work. It goes beyond the small-minded virtues of efficiency and reliability and draws on the large-hearted virtues of the human spirit: generosity and creativity.

Agile At Riot Games

One of the site visits was to Riot Games, the largest e-sports firm in the world. Joakim Sunden, a technical leader at Spotify, will tell us not so much about how wonderful Spotify is, but rather about the site visit to Riot.

Joakim Sundén: Riot Games is an e-sports company that aspires to be the most player-focused gaming company in the world. They currently have one game in production, League of Legends, a team-oriented action and strategy game or Multiplayer Online Battle Arena. The game has dominated the online market since at least 2012 and is the biggest online PC game in the world with more than 67 million monthly active users, 27 million per day, and over 7.5 million concurrently during peak hours.

E-sports is big business. There are professional leagues for League of Legends, just as in football. There are professional players with salaries. The world championship of League of Legends is now bigger than the US Super Bowl. The first prize is five million dollars. E-sports “athletes” can get visas to compete in the competitions and there are scholarships at universities. There are even issues of doping and the use of performance-enhancing drugs, just as in regular sports. For people under 35, e-sports is now more popular on television than live sports.

Riot was founded in 2006 and has 2,500 staff with 15 offices all over the world, from their biggest main office in Santa Monica in the West to Tokyo in the East. Riot Games is a popular employer (e.g. #13 on Fortune’s list of 100 “Best Companies To Work For”), they were Agile from the start and have a trusting culture and decentralized way of operating.

The Riot Games culture: Culture is one of the most important factors why people work at Riot Games. One Rioter explained that Riot culture comes from the experience of being burned by a different culture where managers would say, “You have to do this”. “Here at Riot, you can’t tell anyone to do anything. And that’s not a joke!” Instead, you have to sell it to them. Instead of telling them what to do, it’s all about the mission and player focus.

Mission and player focus: Another key aspect of the Riot Games culture is the laser-sharp focus on their number one target user: “We are defined by our audience: core gamers.” That is also expressed in the company mission statement, “To be the most player focused game company in the world”. You can wake up any Rioter in their sleep and they can repeat it. People typically mention it 10-15 times a day in conversations. It’s actually so important that it’s a requirement when hiring for almost all roles to be a hardcore gamer, although exceptions are made for those with a particular expertise.

People we met at Riot Games often made reference to the mission and the players:

• “This is part of our player promise, so we need to…”

• “If you put something in front of players, you should…”

• “We got to get it into players’ hands before pre-season!”

• “If it doesn’t have a consequence for the player we shouldn’t do it!”

• “How player focused is she?” (Asked in Performance review)

The culture at Riot Games is a sharp contrast with the bureaucratic culture that Gary Hamel was talking about earlier in the conference, where people are just following rules and filling in roles. When Rioters are asked to do something, even follow new policies or guidelines, they will ask themselves if it’s going to help them deliver value to the player. If you can convince them that it is, they will probably do what you say. Otherwise they are likely to speak up and say: “I don’t think that will help the player experience.”

One example is that they don’t do budgeting, only forecasting exercises. If you need to hire people you just go ahead and do it. If you’ve done your homework, and can answer all questions, you’re fine, even if you have already “used” all your forecast headcount.

Another example of this trust and autonomy is how the development manager coordinator we met had produced a video explaining the Development Manager role by internally recruiting people and procuring what she needed without having to seek approval.

Here is the way one Engineering Director puts this: "Your good idea must survive the crucible of socialization to become great. What this means in many cases is that we take a Product Management stance for organizational development: we must understand who is the arbiter of value and how to realize that value.”

To really get to know the players in one of their biggest markets, Riot has installed Korean style Internet cafés, complete with vending machines with Korean snacks, where they encourage everyone to play. Through this, they discovered early on that some features that they thought were important didn't make sense, (e.g., online chat), or proved difficult to use in that environment, (e.g., because players were using a shared computer.)

Crowd-sourcing ideas: It was interesting to hear Gary Hamel talk about crowd-sourcing ideas. Riot Games has a well-defined “Request For Comment” (RFC) process. Anyone can make a proposal for a change. It could be a technical or architectural change, but also an organizational or process change. An RFC is submitted to a central repository. There is an open comment period. Depending on the type of decision, it can either automatically pass, if there are no objections, or it will go to a small group of people who would make a final decision informed by the process. The decision is then communicated across all development teams.

The RFC process is a way to leverage wisdom of the crowd while at the same time socializing change and empowering all. The real structure and governance depends on the type of interaction you desire and the mechanism for formalizing the decision. In a well-crafted system, the best ideas will survive regardless of whose brain they emerged in. Yet, for organizational governance, there may be a small group that harvests these ideas for operations and final approval.

All recently-approved and ongoing RFCs are published in their Engineering Weekly newsletter. These newsletters are also put up in all bathroom stalls.

Overall, the mission clarity and customer focus at Riot is compelling. It gets people to rally around. The user empathy and customer focus is remarkable. The socialization philosophy of change is pervasive throughout this remarkable organization.

Agile At C.H. Robinson

Steve Denning: Now let’s hear from Vanessa Adams about the Agile transformation at a seemingly very different organization: C.H.Robinson. C.H.Robinson is s not a fresh young firm like Riot Games or Spotify. It’s 111 years old and was born in the mid-West of the USA.

And what’s its business? Well, if Uber is a firm that arranges the transport of people even though it doesn’t own any cars, C.H.Robinson is a firm that arranges the transport of goods, even though it doesn’t own any trucks or ships or plans. It’s a transport brokerage firm. It connects people who want to ship something with people who want to receive something. It does that on a very large scale and it has had a large Agile transformation under way for about five years.

Vanessa Adams: Yes, C.H. Robinson is logistics and supply-chain services company. We manage the transportation of freight globally for 110,000 customers; moving goods via truck, rail, ocean and air around the globe. I am in the upper middle layer of management there, and I participated in all the site visits to Spotify, Riot Games, Barclays and the other firms and I am thankful for that.

I joined C.H. Robinson in 2000 when our IT shop was smaller. In those days, we were on a first-name basis with our business leaders.

Since then, we have grown our IT department tenfold and software has become central to our business. With that growth came the challenges of scaling. At first, we did what many organizations have done to cope: we added bureaucracy. As usual, innovation slowed, buried under the weight of the added processes. Our once-close partnership with the business suffered and we began to fall behind. The magic I felt early on with Robinson faded. I began to wonder whether this company that I loved so dearly could possibly get back to the way it was when I joined in 2000.

This is where Agile enters the story. In 2011, I attended a conference. The main Topic was Agile. I started to see why we were having some of the issues we were having. I left the conference with the belief that a journey to Agile could be the cure for what was ailing us. I immediately brought in coaches and consultants and they began to teach us how to “do agile.” I thought this was going to lead us to a better place. In reality it was a lot of pushing and pulling.

Change in a large organization is never easy. We started to see the benefits of Agile but instead of the door being kicked open, it was only open a crack. Despite the Agile practices that we had introduced, we were bogged down once again in more practices and procedures. I still believed in Agile, but I could see that we weren’t realizing the full benefit. But we couldn’t see where or why we were stuck.

In 2015, we heard about the Learning Consortium and we decided to join. Initially I was curious but skeptical. I wasn’t sure that what we could learn about the challenges we were facing from companies that were very different from us.

But after our first set of site visits, I changed my mind. I was really excited. At Ericsson, I was impressed with the amount of transparency that they were willing to share with us. We didn’t sit in a conference room all day. We met with people who were actually implementing Agile and they were very open with how they were dealing with the same kinds of problems that we were concerned about. I walked away with renewed confidence, knowing that we could aggressively move forward with some of our ideas. I was now armed with the shared knowledge of what to avoid and what would work.

This was just one of the IT groups at Ericsson with over a thousand people and their progress was inspiring. They were able to execute some of our ideas even though they were almost twice our size, and I saw it first-hand. It actually worked!

From the site visits, I could now see why C.H.Robinson was stuck. We were in the beginners’ rut of “doing agile” instead of “being Agile.” We were going through the motions; training, education, processes, tools, ceremonies, and iterating over and over again. That was where we needed to start our journey. But let me be honest: it was far from our destination. We still needed break through and solve the complexities we were facing. Our IT department was 600 strong and we had large multi-year projects and commitments. All of our problems came back to one basic issue: we needed more of a shared Agile mindset across the whole group.

I couldn’t wait to share the Ericson story with my peers and the CIO. So I decided to get him on board to join the next site visits of the Learning Consortium. I explained the opportunity that it represented. As I expected, I immediately got an eye-roll followed by a big sigh and several more eye-rolls. At one point, his pupils fully disappeared in an eye-roll. I stuck to my guns and I got agreement, or more precisely, a begrudging “Fine.”

A month later, I found myself on a plane to California with our CIO for the next round of site visits. I have to be honest: I was really nervous. Here I was, visiting Microsoft and Riot Games with my CIO. But after all, Microsoft? I hadn’t thought of them as being Agile. And Riot Games? A gaming company, what could we possibly learn from a gaming company?

I am not a gamer. I didn’t know anything about Riot Games. I was somewhat encouraged when a good friend asked where I was traveling to. I said Riot Games, and he said, “You mean, The Riot Games?” That reassured me that that maybe we were on to something really special.

The site visits to Microsoft and Riot had a profound impact on us. We were amazed at what Microsoft had accomplished in terms of of agility and I would encourage you read the Forbes article, “Surprise: Microsoft is Agile,” which lays it all out.

In addition to a great Microsoft visit, we were astonished at how a gaming company like Riot Games could actually bring a lot of value to our 111-year-old logistics company. We learned that Riot doesn’t even talk about Agile: they focus on their culture and putting the customer in the center of everything they do. As a result, the same CIO who was rolling his eyes at me and assuming it was a waste of time was the same CIO who ended up hugging the Director at Riot Games for giving us the time. In Minnesota we don’t hug, so that tells you something.

So you may be asking yourself what our participation in the Learning Consortium has done for us. We made changes by creating smaller cross-functional teams that could deliver value with minimal cross-team dependencies. We went from an average of eighteen teams needed to accomplish milestones to cross-functional teams that were able to deliver something of value without complex dependencies. We are now consistently delivering value to our branch offices and our customers on a regular basis vs a multi-year timeline. We went from quarterly releases to releases each day.

Our newly-released mobile app was designed for and built by our customers: the carriers. We constantly met with carriers them to get their feedback and ensure that we delivered into their hands an app that would truly make a difference in how they work and live. We stopped talking about the tools and processes of Agile and we focused more on constantly learning and evolving and adding value to customers.

In the process, we found that we were recapturing what we had lost: the elements that had originally made Robinson a truly special place for me. We were back to the close partnership with our business and the immediate feedback showing that we are making a difference.

Agile is not just for IT: We also saw that Agile isn’t just an IT thing. This past May, C.H. Robinson leaders around the world joined us for a two-day conference in which the director of Riot Games spoke and facilitated a group discussion focused on the Agile mindset. Our business leaders who used to meet with us quarterly—if we were lucky—are now meeting with us on every two to four weeks and our entire planning process has changed. It’s not that we have arrived or that we have no skeptics. But we are continually inspecting and adapting and making progress. So I now know that Agile transformation at scale is possible.

Agile for HR: Furthermore, our HR department was highlighted in the Harvard Business Review entitled, “Embracing Agile.” They looked at the successes that we were having in IT and decided this powerful new way of working would help them move faster and deliver their services better and sooner. They understood the way organizations have traditionally managed large personnel initiatives is too slow and rigid in today’s hyper-competitive business environment. They have broken their work down into smaller pieces that can be delivered incrementally.

Agile for marketing: Also, our marketing department is undergoing their own Agile transformation as we speak. Our business executive leadership, HR, and marketing teams are all on their own journey to Agile. Agile is not an IT-only thing. This is a movement that transcends departments and roles. In the end, it’s about making the whole organization Agile.

Perhaps the two most important things that I have gathered from the site visits of the Learning Consortium are these.

First, the Agile mindset. Agile isn’t about the tools or processes or frameworks. It’s about having a different mindset and descaling the work. It’s important that the Agile mindset is instilled throughout the culture. We had set out to figure out how to “scale” Agile to meet the issues facing our large our department. We came to see that this was the wrong way of approaching things. As Jonathan Smart at Barclays said, “Every time you think you need to figure out a solution for scaling, you should start figuring out how to descale. Remember that: flip the script, challenge yourself and descale. Don’t scale your problem up! Break your problem down!” We are now continually looking for ways to strengthen this mindset and descale problems in order to find solutions to complexity through simplicity.

Second, relationships. The relationships I have formed in the site visits to these companies have been far more valuable for our Agile journey than all the conferences, books, seminars, and Agile coaching I have been involved in combined. I have had the opportunity to interact with Agile thought leaders and practitioners on a consistent basis, even outside of the site visits and we are able to discuss openly the challenges we are facing. These opportunities give us the ability to distinguish theory from practice. When none of us are panic about selling or making our team or our company look good, we are free to learn from each another. This is when great conversations occur. Member companies share what’s s working and what isn’t. Their challenges are as valuable to hear about as their triumphs.

What I found was that an understanding of how other companies were working through articles or conferences could only take us so far. It’s the ability to see things first-hand that has made the difference for us. So my advice is, if you want to know what the Agile movement is about, go and see for yourself. Find opportunities to network or go see companies in person. Doing it in a group helps you learn more than doing it alone because it deepens and reinforces the learning. Overall, doing this in the context of the Learning Consortium has been one of the most rewarding experience both professionally and personally.

Agile Is A Journey

Steve Denning: One of the interesting things about the site visits is that all of these firms are on journeys. None of them have arrived. None of them present themselves as having “the solution.” None of them see Agile as a panacea. All of them are facing challenges, even the most famous of them. That can be a reassurance to firms that are earlier in their own journey. Now they realize that they are not alone in encountering implementation issues. And some of the things that they are doing have proved useful to the firms that are further along. So this is very much an collective set of Agile journeys, a set of journey that is inspired by “inspect and adapt” as we continue to learn.

Coming in Part 2: Gary Hamel On Agile

And read also:

What is Agile?

Explaining Agile

Surprise: Microsoft Is Agile

HBR’s Embrace Of Agile

Why Do Managers Hate Agile

The Case against Agile: Ten Perennial Objections

___________________

Follow Steve Denning on Twitter at @stevedenning

Disclosure: I am an unpaid pro bono adviser and director of the SD Learning Consortium.

Fri, 02 Jun 2023 18:30:00 -0500 Steve Denning en text/html https://www.forbes.com/sites/stevedenning/2016/11/26/can-big-organizations-be-agile/ Microsoft is scanning the inside of password-protected zip files for malware

Black and white close up of sinister-looking male eyes looking suspiciously through the slats of a closed venetian blind. Could be a criminal or a stalker or a watchful home owner. — Enlarge

Microsoft cloud services are scanning for malware by peeking inside users’ zip files, even when they’re protected by a password, several users reported on Mastodon on Monday.

Compressing file contents into archived zip files has long been a tactic threat actors use to conceal malware spreading through email or downloads. Eventually, some threat actors adapted by protecting their malicious zip files with a password the end user must type when converting the file back to its original form. Microsoft is one-upping this move by attempting to bypass password protection in zip files and, when successful, scanning them for malicious code.

While analysis of password-protected files in Microsoft cloud environments is well-known to some people, it came as a surprise to Andrew Brandt. The security researcher has long archived malware inside password-protected zip files before exchanging them with other researchers through SharePoint. On Monday, he took to Mastodon to report that the Microsoft collaboration tool had recently flagged a zip file, which had been protected with the password “infected.”

"While I totally understand doing this for anyone other than a malware analyst, this kind of nosy, get-inside-your-business way of handling this is going to become a big problem for people like me who need to send their colleagues malware samples,” Brandt wrote. “The available space to do this just keeps shrinking and it will impact the ability of malware researchers to do their jobs.”

Fellow researcher Kevin Beaumont joined the discussion to say that Microsoft has multiple methods for scanning the contents of password-protected zip files and uses them not just on files stored in SharePoint but all its 365 cloud services. One way is to extract any possible passwords from the bodies of an email or the name of the file itself. Another is by testing the file to see if it’s protected with one of the passwords contained in a list.

“If you mail yourself something and type something like 'ZIP password is Soph0s', ZIP up EICAR and ZIP password it with Soph0s, it'll find (the) password, extract and find (and feed MS detection),” he wrote.

Brandt said that last year Microsoft’s OneDrive started backing up malicious files he had stored in one of his Windows folders after creating an exception (i.e., allow listing) in his endpoint security tools. He later discovered that once the files made their way to OneDrive, they were wiped off of his laptop hard drive and detected as malware in his OneDrive account.

“I lost the whole bunch,” he said.

Brandt then started archiving malicious files in zip files protected with the password “infected.” Up until last week, he said, SharePoint didn’t flag the files. Now it is.

Microsoft representatives acknowledged receipt of an email asking about the practices of bypassing password protection of files stored in its cloud services. The company didn’t follow up with an answer.

A Google representative said the company doesn’t scan password-protected zip files, though Gmail does flag them when users receive such a file. My work account managed by Google Workspace also prevented me from sending a password-protected zip file.

The practice illustrates the fine line online services often walk when attempting to protect end users from common threats while also respecting privacy. As Brandt notes, actively cracking a password-protected zip file feels invasive. At the same time, this practice almost surely has prevented large numbers of users from falling prey to social engineering attacks attempting to infect their computers.

One other thing readers should remember: password-protected zip files provide minimal assurance that content inside the archives can’t be read. As Beaumont noted, ZipCrypto, the default means for encrypting zip files in Windows, is trivial to override. A more dependable way is to use an AES-256 encryptor built into many archive programs when creating 7z files.

Mon, 15 May 2023 12:14:00 -0500 Dan Goodin en-us text/html https://arstechnica.com/information-technology/2023/05/microsoft-is-scanning-the-inside-of-password-protected-zip-files-for-malware/ Twitter accuses Microsoft of refusing to pay for tweets and abusing its data access

Washington CNN —

Twitter is accusing Microsoft of abusing its data access privileges to its platform, in the latest sign of the social network’s owner Elon Musk igniting a feud between the two tech companies.

In a three-page letter to Microsoft CEO Satya Nadella — and sent by Alex Spiro, Musk’s outside lawyer — Twitter accuses Microsoft of over-using its ability to get tweets from the platform, in an alleged violation of the social media company’s terms.

Microsoft products, including Xbox One, Bing, Azure, Power Platform and Microsoft Ads, have “retrieved over 26 billion tweets in 2022 alone,” according to the letter, a level of usage it said could be considered “excessive or abusive.”

“Our accurate review of Microsoft’s activity on the Microsoft Apps indicates that Microsoft may have been in violation of multiple provisions of the Agreement for an extended period of time,” said the letter, a copy of which was reviewed by CNN, and referring to Twitter’s developer agreement.

The letter also listed a number of other alleged violations, including an apparent failure to state a purpose for some of Microsoft’s data collection and, in other cases, use of the data in connection with “automation capabilities” subject to Twitter restrictions.

The letter comes as Twitter is racing to find ways to boost revenue and cut costs after Musk took on a significant amount of debt to help finance his $44 billion acquisition of the company.

Microsoft refused to pay Twitter to maintain its data access through Twitter’s application programming interface (API) after Twitter erected a paywall seeking to charge for data, according to the letter. The letter called on Microsoft to provide information about its past two years of Twitter API usage, setting a deadline of June 7.

“We heard from a law firm representing Twitter with some questions about our previous use of the free Twitter API. We will review these questions and respond appropriately,” a spokesperson for Microsoft said in a statement. “We look forward to continuing our long term partnership with the company.”

In accurate months, Musk has stepped up his criticism of Microsoft as a perceived rival in artificial intelligence development, a field that relies heavily on ingesting publicly available online content such as tweets.

After Twitter announced plans this year to charge for API access — which organizations later learned could cost them as much as $210,000 a month — Microsoft’s advertising platform said it would no longer support integration with Twitter.

Musk reacted with a tweet saying Microsoft had “illegally” used Twitter data to train its AI and warned it was “lawsuit time.” He also accused Microsoft of “ripping off the Twitter database, demonetizing it (removing ads) and then selling our data to others.”

In another tweet earlier this year, Musk blasted OpenAI, the maker of ChatGPT, for being “effectively controlled by Microsoft.” Microsoft has invested billions in ChatGPT’s creator OpenAI and integrated ChatGPT into its Bing search engine. But Nadella said this week in an interview with CNBC that Musk’s claim about control is “factually not correct.”

“We have a noncontrolling interest in it, we have a great commercial partnership in it,” Nadella said of OpenAI.

Musk’s targeting of Microsoft over its AI investments appears closely linked to his overall criticisms of existing AI models. Musk has vowed to develop a rival AI he calls “TruthGPT” to counter what he has described as excessive political correctness in mainstream models.

Fri, 19 May 2023 05:04:00 -0500 en text/html https://www.cnn.com/2023/05/19/tech/twitter-microsoft-data-access/index.html Systemic Challenges to Implementing Universal Basic Income

2022

Overview

A growing body of evidence shows that implementing universal basic income (UBI), or guaranteed income programs, would create a public assistance system that more effectively promotes food security, improves health outcomes, and creates long-term financial stability. However, executing this type of program on a larger scale outside of pilots has been difficult, due to an issue known as the “benefits cliff effect.” The risk of participants losing Social Security Administration (SSA) assistance such as Social Security Disability Insurance (SSDI) or Supplemental Security Income (SSI), as well as the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF), Medicaid, and housing assistance has been a major barrier in implementing UBI. These benefits are incredibly difficult to get in the first place due to strict eligibility requirements, and loss of benefits can have detrimental impacts for program participants. This policy brief provides a framework through which cities and states can understand public assistance programs and recommendations to execute UBI or guaranteed pilot programs to better support families.

Background

Public Assistance

The public assistance system in the United States is fraught with red tape that prevents people from receiving much-needed aid. Public assistance programs have historically been inadequate to support families in meeting their basic needs, leaving many food-insecure. Means-tested public assistance programs—such as SNAP, TANF, and Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)—have different eligibility criteria and rules of participation and require a great deal of paperwork. These create significant time and administrative burden for both program recipients and the state and federal government agencies administering the programs.

Furthermore, TANF benefits vary significantly from state to state and are at or below 50% of the federal poverty line in every state. Participants of the SNAP program have said that the level of benefits is not enough to support a nutritious diet for families, and benefits can be extremely difficult to obtain. Due in part to the work of the SNAP Participants Collaborative and Center for Hunger-Free Communities, in 2021 the U.S. Department of Agriculture raised the SNAP benefit allotment by 21 percent for the first time since 1975.

Universal Basic Income

Universal basic income has been shown to promote overall health and well-being, with participating families reporting higher rates of food security, improved mental health, and increased ability to pay bills. (For more information on the case for UBI, see the Center for Hunger-Free Communities’ report “Universal Basic Income: Key to Reducing Food Insecurity and Improving Health,” February 2021)

The accurate child tax credit, which functioned similarly to guaranteed income programs, proved to be effective in decreasing childhood poverty, reducing food insecurity, and allowing families to access basic necessities.

To prove the efficacy of programs such as UBI or guaranteed income in promoting food security and helping families move out of poverty, organizations such as the Mayors for Guaranteed Income and University of Pennsylvania’s Center for Guaranteed Income Research have launched pilot programs. However, one of the major barriers to implementing these pilot programs is the risk of participants losing benefits from the Social Security Administration (SSA), as well as SNAP, TANF, Medicaid, and housing assistance.

Key Terms and Definitions

Benefits Cliff: A sudden loss of income or public assistance caused by an increase in income.
Guaranteed Income: A government program of ongoing, unrestricted direct cash transfers to individuals or households. A guaranteed income may or may not meet basic needs or be targeted to specific populations.
Means Testing: An evaluation determining whether a person or household is eligible for a payment or public assistance that is based on the person or family’s income and assets.
Supplementary Security Income (SSI): SSI is a monthly public assistance program that provides income to people with limited income who are blind, disabled, or aged 65 years or older.
Social Security Disability Income (SSDI): SSDI provides monthly financial assistance to disabled people and their families if they are insured, which occurs after a person works long enough to qualify (typically 10 years) and paid Social Security taxes.
Universal Basic Income (UBI): A government program to ensure a basic standard of living and economic security for every member of a community through monthly, unconditional direct cash transfers with no means testing.

The Benefits Cliff

The benefits cliff refers to when someone experiences a sudden loss of public assistance because they start making a higher income. Even a small increase in wages can result in benefits such as SNAP or TANF being cut off, which prevents many program participants from building wealth and meeting their own basic needs. SNAP participants have reported that a loss of benefits causes a collapse in financial well-being, causing increased food insecurity, health care trade-offs, and more precarity.

The negative impact of the benefits cliff is compounded by the immense amount of time, energy, and resources that families spend to get their assistance back once it is lost. This discourages many people from taking on promotions or full-time work. Families who saw even a marginal increase in income lost their SNAP benefits and had difficulty purchasing food for their families.

The effects on health are also significant with the benefits cliff. As families use their limited income on food rather than relying on SNAP, there is an increase in health trade-offs (e.g. seeking medical care) as well as increases in depression and mental distress.

The loss of income or public assistance is especially troubling for people with disabilities. One in four SNAP participants has a disability or receives government disability assistance. Because SNAP defines disability status differently than the SSA, disabled people may face barriers to obtaining SNAP. Furthermore, disabled adults are twice as likely as those without a disability to experience poverty, with disabled adults being disproportionately vulnerable to being priced out of housing.

Social Security Benefits

Social security is a public assistance program with nearly universal public support. Both SSI and SSDI provide critical financial support to families with limited income or those with disabilities that preclude them from working. Food insecurity is also an important consideration for SSI and SSDI participants. Households with disabled adults are more likely to experience food insecurity; these households are also more vulnerable to severe food insecurity.

Additionally, many low-income non-elderly adults do not qualify for benefits but are still unable to work due to their disability. Guaranteed income programs would exist alongside SSI or SSDI to better support households experiencing deep poverty and food insecurity.

Social security programs are vital for the survival of low-income and/or disabled adults in the U.S. Data show that SSI applicants typically have significant declines in health status prior to receiving assistance, followed by relative stabilization. Social security is effective in reducing poverty for children, the elderly, and families, and especially for women and families of color.

Losing social security assistance can have catastrophic effects on the mental and physical health of families. For example, participation in a universal basic income pilot could increase a family’s income and make them ineligible for SSI, which could leave families vulnerable to food insecurity and worsened health.

How is SSI obtained?

SSI is available to eligible adults residing in one of the 50 states or District of Columbia and select lawful permanent residents. Assistance can be applied for online or at SSA offices.

How is SSDI obtained?

Workers who were in jobs covered by social security and meet the strict definition of disability are eligible for assistance. Disabilities that qualify include any ailment that limits an individual’s ability to complete work-related activities for at least 12 months.

Why are benefits so difficult to get?

When social security was first implemented in 1965, it was intended to function as supplemental income. Today, more Americans than ever are relying on the program as their primary source of income, leading to limited resources for the program. Furthermore, many first-time applicants for SSDI are denied, due to the strict eligibility requirements and required documentation.

Potential UBI Impact on Public assistance in Pennsylvania

Public Assistance Program	Eligibility Requirements	Pilot Program Impact on Assistance
Supplementary Security Income (SSI)	Little to no income; possessions valued at less than $2,000 for individual or $3,000 for couple	Participation in UBI/guaranteed income pilot could impact SSI eligibility
Social Security Disability Income (SSDI)	Applicant must be a worker or adult child of a worker who cannot work due to disability; disability must have lasted for at least a year and continue for at least a year or lead to applicant’s death	SSDI eligibility is based on historic inability to work, and UBI/guaranteed income would not impact SSDI eligibility
Temporary Assistance for Needy Families (TANF)	Applicant must have low income and assets valued at less than $1,000; income includes unearned gifts	UBI/guaranteed income would impact TANF eligibility and other benefits linked to TANF (e.g. child care and transportation)
Supplemental Nutrition Assistance Program (SNAP)	Applicant must report both earned and unearned income	UBI/guaranteed income would lower monthly SNAP benefit allotment
Medicaid	Individuals can qualify through Modified Adjusted Gross Income (MAGI) requirements or by being elderly, blind, or disabled	MAGI groups not impacted; non-MAGI groups would count UBI/guaranteed income towards eligibility
Section 8 Housing Vouchers	Family income cannot exceed 50% median income in county or metropolitan area	UBI/guaranteed income payment could impact Section 8 eligibility

Adapted from the Pennsylvania Benefits Matrix provided by the Humanity Forward Foundation

UBI and Public Assistance: The Stockton Pilot Program

As universal basic income gains momentum as an effective and sustainable solution to supporting families’ long-term economic security and overall health, pilot programs in cities like Stockton, California, have demonstrated the benefits of guaranteed income.

Researchers of the Stockton Economic Empowerment Demonstration (SEED) had several loss mitigation strategies to run their experiment alongside means-tested public assistance programs, instead of replacing them. In the enrollment process, SEED staff addressed households rather than specific people so household members could decide who should participate. SEED also included benefits counseling for potential participants, a cost-analysis sheet outlining how public assistance could be impacted, and ongoing communication with SEED staff.

Researchers also secured a waiver with the San Joaquin County Human Services agency to ensure CalWorks and TANF program participants could participate in SEED without the risk of losing their assistance. SSI was still at risk of being impacted, so recipients could decide to participate based on the cost-analysis. In addition, a Hold Harmless Fund was established to ensure that recipients weren’t negatively impacted through their participation in the program, replacing the cost of any lost assistance.

To protect against the loss of assistance, pilot program researchers held discussions with local and federal government officials to explore options such as implementing waivers for guaranteed income payments or disregarding payments when considering eligibility for public assistance programs.

Policy Recommendations

To support the health and well-being of public assistance participants and reduce the administrative burden of these programs while allowing for the effective utilization of universal/guaranteed income programs, we recommend implementing the following policy changes.

Develop a centralized public assistance program with uniform eligibility requirements and safeguards to support low-income families which will provide a sustainable path to food security and financial stability.

With each assistance program having different eligibility requirements, it is time to create a universal public assistance program through which all funding can be administered. While universal basic income would create a sustainable, comprehensive safety net, cash payments should work alongside other public assistance programs for the time being. By creating universal guidelines, public assistance will not only be easier to obtain for those in need, but the significant administrative burden would also be reduced.
Implement a national waiver that ensures universal basic income or guaranteed income pilot program participants do not lose public assistance.
Developing a federal waiver would ensure UBI/guaranteed income program participants do not lose existing public assistance supports, regardless of the city or state in which they live. By incorporating a guideline that prevents assistance like SSI, SNAP, or TANF from being cut off and leaving participants vulnerable to the benefits cliff, participants could take advantage of direct cash payments to feed their families, pay bills, and promote their health.
Create an alternative to the benefits cliff by easing participants off of assistance.
Creating a solution that does not cause a steep drop off of assistance programs when participants increase their income will safeguard against precarity and support families in the pursuit of food and economic security. Ideally, funding would be lowered gradually instead of ending abruptly, in proportion with income increases over a period of time, providing participants the opportunity to stabilize their income and move off public assistance programs permanently.

For more information, contact: Kasia Kujawski, Dornsife Fellow, at kk3397@drexel.edu or Mariana Chilton, PhD, MPH, Director, at mariana.chilton@drexel.edu.

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Building livelihoods

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Overview

Background

Public Assistance

Universal Basic Income

Key Terms and Definitions

The Benefits Cliff

Social Security Benefits

How is SSI obtained?

How is SSDI obtained?

Why are benefits so difficult to get?

Potential UBI Impact on Public assistance in Pennsylvania

Public Assistance Program

Eligibility Requirements

Pilot Program Impact on Assistance

UBI and Public Assistance: The Stockton Pilot Program

Policy Recommendations

Develop a centralized public assistance program with uniform eligibility requirements and safeguards to support low-income families which will provide a sustainable path to food security and financial stability.

Implement a national waiver that ensures universal basic income or guaranteed income pilot program participants do not lose public assistance.

Create an alternative to the benefits cliff by easing participants off of assistance.

How To's &amp; Resources

Get Support

Building livelihoods

Providing water, sanitation, and hygiene

Advocating with and for communities

How To's & Resources