The following are the outputs of the captioning taken during an IGF intervention. Although it is largely accurate, in some cases it may be incomplete or inaccurate due to inaudible passages or transcription errors. It is posted as an aid, but should not be treated as an authoritative record.
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>> So at this time, we would like the honourable Larry Irving to present testimony.
>> Thank you, Mr. Chair. I would like to thank you and members of the subcommittee to testify today on findings of defining the digital divide and the study of release by the commerce department earlier this month. President Clinton and secretary daily released in Los Angeles during the president's new markets tour. And during the tour the president and secretary Daley discussed fag even though the nation in technology underlies the technology growth, far too many Americans remain out of the digital economy. The digital divide, the have and have not has become a critical access and right issue. Access to technology such as the computer and internet will be the key to success of any American business, community and individual.
Increasingly Americans use it to find jobs and locate technology and take course online. The electronic companies are helping small companies compete in underserved areas remote to the rest of the world. New Year's Eve technology will prepare Americans for the high-tech workplace of the 21st century. Because of the role, is being daily ensured that the access to tools for the digital economy is one of the best thing that the economy could make and it become essential all Americans urban or rural, black or white, Hispanic and Native American can reach these new technologies. It provides a starting point between rich and poor. This is our third report examining census data looking at the digital divide. And we anticipate it will serve as an important diagnostic tool to assist policy makers in the policy sector to provide more access for more American.
Today I would like to provide for the subcommittee several slides showing key findings. Niece slides show overall Americans are far more connected than they have been in years past. On the other hand, we have also found there are alarming disparities based on income and technology and race and geographic location in which Americans have computers and who is online. Kind of interesting as I read my testimony.
Equally disturbing many disparities are growing. Let me turn to the first slide. This shows --
>> Sir, everyone will be in the dark if we don't get online.
>> JAISHA WRAY: Great. Thank you all for joining us today. My name is Jaisha Wray. I'm the Associate Administrator for the Office of International Affairs and acting for policy development in the National Telecommunications and Information Administration, NTIA, in the United States. What you just saw was a video from NTIA discussing the early days of measuring internet use in the United States.
As you will hear this issue continues to be of high importance and the work continues on to this day as well. Today we have distinguished set of speakers from NTIA and the US Census Bureau who will discuss the past, present and future of measures internet use in the United States.
Located within the US Department of commerce, NTIA is the executive branch agency principally responsible by law for advising the president on telecommunications and information policy issues. And NTIA's programmes and policy making focus largely on expanding broadband internet access and adoption in America, expanding the use of Spectrum by all users and ensuring that the internet remains an engine for vague and economic growth.
Also located within the Department of Commercial, the federal bureau is the largest federal agency with providing equal data about nation's people and economy. The Census Bureau provides high equal, timely and relevant data products that determine how legislative seats are described across the nation. And policy making and planning about community services and annual distribution of federal funds to state and primary governments.
Together, experts from these agencies mostly detail how they measure internet use, highlighting promising new initiatives and issues that require further commanding in this ongoing effort. Following their overview we want to open the floor for robust interactive discussion with both people in the room and online. We want to hear how other countries are measuring internet use and what we can learn from their experience.
In particular what are the missing piece insides measuring internet use? And how can the international community collaborate in this space? We hope that this open forum will serve as an opportunity to bring experts from around the world together to advance the state of knowledge for one of the most important aspects of digital connectivity, understanding how people use the internet.
So to kick things off, I will ask my colleagues to briefly introduce themselves.
>> MODERATOR: Good afternoon. My name is Susan Chalmers and the Internet Governance team lead at the Office of International Affairs.
>> LUIS RAMOS: My name is Luis Ramos. Senior Policy Advisor, Office of Policy Analysis and Development, NTIA.
>> ONLINE MODERATOR: I'm Andrew Flavin, the Digital Policy Team Lead from the Office of International Affairs.
>> RAFI GOLDBERG: Good afternoon. My name is Rafi Goldberg, and I've been working on policy in NTIA for the past 13 years. And I will pass it on to the Census Bureau friends.
>> Great, thank you, Rafi. My name is Leslie Davis and I'm the subject matter expert on computer and internet use as measured by our surveys.
>> Good afternoon. I'm Heather King. It's morning for us. I work in the same division with Leslie and you will meet Mike after me. They are the subject matter experts on internet and computer use. And I bring molding expertise to the table. I will pass it to you, Mike.
>> MODERATOR: In terms of our run of show today we will first hand it over to Luis to discuss the survey and its history. Following that, Leslie will talk about the US Census Bureau's decades-long work in the community survey. After Leslie, Rafi will highlight the latest project to produce local estimates of internet adoption.
Heather will then dive deeper into the technical details of this project. And following the presentation, Susan and our other subject experts will help steward the forum discussion. So with no further adieu, we will get started and over to Luis.
>> LUIS ZAMBRANO: Great. Thank you so much, Jaisha. I will look to the field for the NTIA internet use survey. This survey is a popular survey sponsored by the US Census Bureau and the US bureau of statistics. It is a monthly survey primarily known as a source for. So our labour statistics. Agencies such as NTIA have such mental questions in particular months. Tens of thousands are done every month providing a large nationally representative sample of American households.
We have worked for over 30 years with our partners at the Census Bureau on this survey. The internet use survey is the longest running survey on computer and internet use in the United States. We have sponsored a grand total of 17 surveys in the field since 1994, and we are planning to get our next survey out in November of this year.
So here you can see a timeline of our collections. Over time we have transitioned from print publication of our findings to a more Websterred approach to present the results. And we have block posts and other analysis of the data. And we also have a nifty publicly available explorer tool that I will showcase in a bit.
One very important component of the NTIA is to obtain the public strum itself. We include a draft survey of the instrument and seek public comment from the public before we issue the survey. This forum, actually is particularly time I will, given last week on June 17th, we published a notice and request for comment for our upcoming survey later this year in 20225.
So with all of this said, what can are learn from the survey? So in addition to learning just about internet use generally, we can also learn things like devices and internet access technologies, details about how people use the internet, including locations and certain online activities. We also have other questions such as questions centered around potential privacy and security concerns that may effect internet use.
Here's a slide of overall internet use showing time and the population. This is the data using our exploratory tool which I will show you in a bit.
The slide breaks down device usage. Perhaps not surprisingly, for example Smartphone use has gone up since 2011 and computer use has decreased.
And here are a few online activities that we have measured, and how they have trended over time. Things like social media use, telework and the like.
So as I mentioned, we have a publicly available explorer tool that we call the NTIA explorer that allows us to play with this data. For example, if I am searching for a device use, specifically laptop use, you can look at that information throughout the years. Can you look at the total number in millions and percentages over the years. You can also get a table that gives you a rule for each of the US states and breaks them down along with numbers, percentages and also things like confidence intervals.
Again here is how the tool is being applied. I any we are having technical difficulties but moving on to the availability of this data, if you want to dive deeper we make all the underlying raw data publicly available and we have a repository with sample code. And at the end of the presentation we will actually give a link to our website. And there you can see some of the publicly available datasets that we have.
And before I pass it on to my census colleagues, last year we actually celebrated the 30th internet use survey. We threw a party. You saw that slide. And we were able to put it on a indication. Unfortunately there is no cake today but I welcome you all to join in the celebration. And with that I will pass it on to my colleague Leslie.
>> LESLIE DAVIS: Thank you so much, Luis. In addition to the internet use survey, the access to the community use sir way or the ACS which is the demographic survey. This is a nationally representative survey that serves as the premier source for timely detailed population and housing information for the U.S. And it provides local and national leaders with information needed for programmes, economic development, emergency management and more.
It is fielded annually to a sample of 3.5 million households nation-wide and also additional group care quarters. And it asks questions on over 40 topics including internet access. And next slide, please.
So in 2008, US Congress directed federal agencies through the broadband data improvement act to improve their data collection on broadband users description. And this act specifically called upon the Census Bureau to add questions to the ACS that measured A, whether persons at households use or own computers at their address, and B, whether persons at that address describe to dial--up or broadband internet service at their address. The computer and internet questions were added to the ACS in 2013. Next slide, please.
So the initial set of questions that were asked on the ACS are shown on the left-hand side of this screen. And they were designed to capture computer ownership, internet adoption as we measure by connection to the internet and internet subscription type.
As a result of us measuring adoption, the ACS data does not offer insights on the level of internet use within a household or the extent to digital literacy skills of a particular respondent.
Furthermore, if a respondent says they don't have a subscription, the ACS data doesn't tell us if there is an internet service provider, thus not allowing for a subscription or if it's due to another reason, such as the cost of the subscription. The ACS questions were revised in 2016, which you can see on the right-hand side of the screen. And their current versions remain as they were in 2016.
These things that we made were implemented after feedback received from survey methods experts and undergoing thorough content testing. And the changes were aimed to address potential execution with question wording, response categories and definitional clarity. The first question will you see on the screen is our changes to device ownership question. And given the focus of today's talk I will switch to the next question, which asks about internet access.
Here we replaced the language regarding subscriptions to paying a provider or cell phone company, which refrains what it means to subscribe or adopt to the internet for respondents. Next slide, please.
As for internet types question, we altered the language of mobile broadband plan to cellar data plan for clarity. In this change alone improved our response reliability drastically. We also collapsed the high-speed categories of cable, fiber and DSL to improve question clarity and also distinguish advocate gore which is fixed to a particular location and compare it to the mobile broadband option.
Again here we removed language related to subscription and changed it to access to the internet which improved our response rates. And as you can see on this question and the device-type question before, we also offered the opportunity for respondents to write in a particular internet service type or device type they may not see on the questionnaire. Clear contact can rewrite these as best as possible and reassign those write-ins as needed. So for example if a respondent wrote in Comcast for a internet service type which is a provider of cable and fiber and internet in the United States, we can typically assign that respondent to high speed broadband on the back end. Next slide, please.
Based on the ACS, the Census Bureau published 1-year and 5-year estimates. And the main difference between the two is the level of geographic regularity captured in the estimates. Our one-year data can go down to the county can place levels for the geography that match. Our population threshold of 65,000 and over which helps ensure confidentiality of respondents and ensure reliability.
The five-year data which brings down 60 month of data can bring down to the census tract and block level as can you see from the hierarchy on the screen. Next slide.
Tables on the screen provide some context for how small these geographies are. So for the one-year data the counties are sub-state geography. They are highly available in geographic area and population size. For example, Los Angeles county in California has about 10 million residents and Armstrong County in Texas has about 2,000. Count industries some government oversight in other states. Places on the other hand represent a town or a settled concentration of people within a state, and can often be identified by name. They sometimes have governmental functions and their median size is about 1,000 people.
Our five-year data can go down to the tract level which is generally represented to be neighbours. They have an optimum size of about 4,000 people. And even smaller than that is the block group. The block group is a group of -- come applies of blocks which is statistical areas founded by visible and non-visible boundaries and they are comprised of about 600 to 3,000 people.
As I mentioned the one-year data is less geographically granular which helps us ensure the reliability of those estimates and our confidentiality of survey respondents. So as a result we were able to publish 27% of counties and 2% of incorporated places in our nation for the one-year dataset in 2023.
Our five-year data in contrast has a greater sample size and better reliable for smaller geographies and as a result we were able to publish all estimates.
Next slide, please. Using the ACS computer and internet data that we collect, the bureau publishes 14 tables on device ownership and internet adoption. Geographics and breakdowns. The data is available on our data tool which is data.census.gov and the data can have pretabulated products and use custom maps as I did to create the map on the screen here, which shows the percent of people aged 65 and older with a broadband subscription in computer by state.
In addition to the tables and maps data users can use our public use micro data sample or comes data to create custom tables. This comes as subsample of the ACS micro data. And it goes through many disclosure processes to protect confidentiality.
Next slide, please. In addition to our pretabulated products, we also produce written reports based on the ACS data. This most recent report elected computer and internet use trends between 2013 and 2021. It also explored disparities in broadband adoption at the county level, and included a great section on the demographics of Smartphone only household in the United States.
Next slide. We also offer shorter block style publications called American categories and here I have two example, one pertaining to tablet ownership among household with children and the other exploring broadband adoption disparities among tribal household.
Next slide. So what are the strength of the ACS data? As I mentioned, it has a large sample size which allows us to publish geographically granular data.
So for example if you are interested in studying broadband adoption at the subsimilar level, the five-year data from the ACS could help you get there. Additionally, the ACS offers detailed demographic data for substrate policies which helps policy makers and more explore adoptions by different fact to fors like income, education and rurality.
We also publish the data on a frequent basis, on an annual basis and it undergoes various verification and checks prior to us publishing it and provides a he helpful time series of data as it dates back to 2013.
>> RAFI GOLDBERG: Thank you, Leslie. Hopefully my first slide is up. Although I condition see it at the moment. But -- you know the NTIA internet use survey and the ACS -- thank you. Has served as the basis for a ton of important research and analysis for many years now. And they continue to be violating data sources for understanding internet use in the United States.
We are also very much aware that these surveys alone are unable to answer every relevant question. And recently we have been spending a lot of time thinking about how to address some of the gaps in our data and to ensure we are fully equipped in the future to understand our progress and challenges.
Next slide, please. We learn a ton from household surveys. But they are not without their lymphs. For example, it's pretty common for colleague or member of the public to ask what internet use is like in their areas and unfortunately the question is limited. Even with a huge sample size ever our surveys those numbers start to get small very fast if you try to Zoom in too far on the map.
For less populous areas as Leslie mentioned we need to get five years worth of ACS data.
You know even if you can work with the three basic internet use questions that are on the ACS, five-year estimates, while very useful in a lot of cases, are not ideal when you are trying to understand the impacts of relatively fast changes, like the introduction of a new programme.
I'm excited to say that NTIA and the focus bureau are working to fill this gap for the presentation. But just so you know we have other challenges in this field. For example while our surveys have high response rates, they have been falling over time. And there's a lot of work on us to try to address that.
Internet use is also very much a field where the technologies and even the word that we use to describe those technologies are changing all the time. So it's always a balancing act between keeping up with those changes in our surveys and being careful not to break that time series comparisons.
Finally while we have data onion line activity through the Internet Use survey we are limited to introduce workforce and other skills. Next slide, please.
So I want to focus now on the problem of getting more granular internet use estimates. And I'm excited to report that last fall, NTIA and the Census Bureau launched internet use and adoption programme or project LEIA. With project LEIA, the technology is to advanced you might think they are from a galaxy far, far away. Next slide, please.
So what exactly is project LEIA? The Census Bureau team is making it possible for us to learn about internet use at the more local level. The first product of this effort was released back in September and the form of the first ever experimental single year estimates of household internet adoption for every county in the United States.
For comparison, only about a quarter of us counties have a large enough population of internet adoption using the single year ACS product. And again the five-year estimates are also able to do. This and they are very useful but not ideal in a lot of situations.
Next slide, please. The basic idea behind small area estimation is that you take what you already know from survey data and feed that into a model alongside other data point that are known to be linked with the outcome of interest. In this case we know from previous studies that factors like income and the availability of broadband infrastructure are predictors of internet adoption rates. So we can work with those as auxiliary data sores. Heather will go into more detail about this in a moment.
But by incorporating the data point with survey estimates you get estimates with smaller margins of error compared with the survey estimates alone. And you also reduce the risk that individual respondents in less populous areas can be reidentified by the publication of new estimates.
That makes it feasible to publish reliable estimates for places with smaller populations. All without having to interview any more households or putting anyone's privacy at risk. Next slide, please.
For our first experiment with this, the Census Bureau team was able to estimate the proportion of households every US county that had a wired internet subscription in 2022. We were really excited to be able to share these first results with the world last fall. And we putting to an interactive map on NTIA's website to show off these new estimates. As you can see there's a lot of adoption rates in these countries and they Zoom in on a particular area of interest. Next slide, please.
While this is a promising start, we think there's a lot more that can be done with project LEIA and NTIA and the Census Bureau are working together on the next steps.
At the same time, we released the feasibility study and estimates, NTIA put out an RRSV with the internet use. Right now we have three tests as part of this initiative. First the Census Bureau team is looking at ways to refine the model for the current set of estimates to get to a point where we all feel ready to shed the enter mental label. And second they are exploring the possibility of improving estimates at the census track level. And as mentioned before, census tracks in the United States are basically neighbours in a lot of places and they generally contain between 1,000 and 8,000 people.
And finally they are working to apply machine learning to bring some of the more detailed computer and internet use data from the NTIA internet use survey to the ACS dataset. Opening up new research opportunities and setting the stage for the potential for small area estimates of those more detailed variables in the future.
We are very excited about the potential for project LEIA to help improve our understanding of internet use in the United States. And I'm pleased to turn next to Heather who will get into some of the more technical details of how the Census Bureau is making lists all possible.
>> HEATHER KING: Thanks, Rafi. I will continue our internet use project with project LEIA. Project LEIA is looking at all counties for measured time for quickly than what the five-year ACS estimates can tell us. So the nearest alternative we could publish the survey estimate from one year from the ACS but as Rafi and Leslie talked about earlier you would only get about a quarter of all counties. So project LEIA using small area modeling techniques allows us to blend that survey with other sources lycra if I pointed out to publish internet adoption rates for every single county in the United States. That is 3,144 I think it was last count.
So next slide. The smaller modeling technique we use -- this is a very high level view of what that looks like. The LEIA model estimates are really -- the definition of two separate estimates of internet adoption. So on the left-hand side of the slide you see that one component is that ACS estimate, that is just from the survey by itself. The proportion of county households that have adopted internet. And on the right-hand side, is what we call the indirect estimate. And this is the mechanism that we use to bring in the other related data sources and other factors that are related to internet adoption.
So this is a regression model where the outcome is internet adoption at the county level. And the predictors are median household income for the county. Proportion of the population with a bachelor's degree or my higher and the proportion of county household that have access to broadband infrastructure, which is taken from an administrative source that measures broadband internet infrastructure from another agency. We could talk more about that if you like.
So taking these two separate estimates of internet introduction, we blend them together, where the contribution of each is determined by the relative precision compared to one another.
Next slide, please. So here's another look at that same visual where we see what happens in larger counties like LA council where we have a population of around 10 million people. The ACS direct estimate proportion of household with internet adoption would be pretty reliable, because we would sample a lot of household from this county. Because it's a very large county, we would send out a lot of questionnaires and we would get very good data from this county because of its size.
So the final model LEIA estimate we would expect a higher contribution from this high equal direction survey estimate where we ask the households directly, do you have access to an internet broadband subscription?
So the LEIA mold would drive more information from the ACS compared to the regression model defined in the indirect estimate.
Next slide. So you can imagine for smaller counties like the one in Texas Leslie talked about earlier, we would expect more contribution from the indirect estimate. Because the ACS estimate for that county, we wouldn't have a lot of cases to derive an estimate from. So the resulting estimate of proportion of household would be rather noisy. This will be reflected in the weight that combines the two estimates, the direct estimate from the ACS and the indirect estimate that brings in the additional data.
Here the indirect estimate we would expect to contribute more for the final estimate for that particular county. Okay. So that's in a nutshell how project LEIA works. So the next slide...
This is the same map that Rafi showed you. This is just a screen shot from our feasibility report. Exact same data but if you want to interaction with the data will you go to the NTIA website to look at didn't views. Zoom in and Zoom out. So just kind of a reminder of what exactly are we molding here. And this is from the actual questionnaire in ACS. So we are modeling the proportion of all households in each county that subscribe to high-speed broadband, internet service. That is cable, fiber optic or DSL, just as reminder. So this is -- so darker blue will be those that have higher proportions of households that have adopted internet for that particular technology type.
Next slide. Okay. So this is just kind of the typical QC done in smaller area modelling. What we are looking at here is a scattered plot that come pairs the proportion of county households that adopt internet, compared to that derived from the LEIA estimate. ACS is on the model and the LEIA proportion is on the Y Axis.
So each one of these circles represents the county. So whenever the LEIA proportion is exactly the same as the survey proportion the circle will fall exactly on that diagonal line. So we don't expect all counties to fall exactly on this line, but generally we want them to follow the general trend.
You see some outliers, some counties, some circles that are not very closely aligned to the line. This means that the ACS data is -- doesn't have a lot of impact here. The model is drawing more from the indirect estimate here. And these are probably going to be very small counties.
So this kind of -- a handful of points away from the line is completely expected. But we see in general the two estimates agree. And this is as desired.
So overall the LEIA model proportion agrees at a high level with ACS.
Okay. Next slide. So this is kind of repeating what Rafi was talking about. And what we are looking to continue with project LEIA we will fine-tune this county model for all counties for internet adoption. And we will get some other useful predictors that we didn't use before, that we got from our request for comments from the public. And namely, we are going to look at measure of urban versus rural. We tried some of those before, but they didn't work out. So there are other ways can you measure that. So we will continue exploring that.
We are going to look at measures of economic growth and concentration of the type of jobs or outcomes in the county, namely science, technology, engineering and mathamatics or stem.
So we will finalise that model and stabilize and have an official product that measures internet adoption. And what we also want to look at feasibility going even further, with granularity and look at below county level census tracks, Rafi and Leslie described. These are subdivision or neighbours of counties around 4,000 people.
But these are statistical entities that the Census Bureau creates at the start of each decade that are generally stable. So it allows people to measure change in a small area over time throughout a decade. And they are redrawn at the beginning of every decade before the census is taken in.
And then the next part, NTIA internet is an offshoot of project LEIA but this is a different set of modelling techniques here. We want to due -- as Rafi mentioned earlier machine learning techniques to explore getting more granularity for those more detailed reasons for how people use the internet and why they don't when they respond that they don't use the internet in the internet use survey. So that is it for our future directions. I will turn it back over to Luis. Luis great. Thank you so much, Heather and that concludes our presentation. I have put up our website and contact information and I pass it over to Susan and Andrew to help us further in the discussion.
>> MODERATOR: Thank you so much, Luis, and thank you to everybody for joining us for open forum today. During this session we have learned from colleagues at NTIA as well as colleagues from the US Census Bureau on two different surveys. First we had NTIA's internet use survey. And then second we heard from the Census Bureau on the American community survey. I would just like to pause to see if anybody has any questions they would like to put forward to our colleagues in person and in Washington, D.C. Sir, please. You may have to use the microphone. Are you welcome to...
>> QUESTION: Hi. Do you hear me? My name is Nana Dorich. And I would like to ask if the NTIA looks at electricity from -- electricity users or CNIT -- for NTIA as such. And do you compare your statistic or use data for commercial provider from FCC or another source that has this information of or do you use them or compare your findings with them. Thank you.
>> MODERATOR: I will just pause to see if colleagues were able to capture the question. Rafi?
>> HEATHER KING: From the Census Bureau we have lots of different sources that we could potentially use that are collected by other agencies. Not specifically the consumption from data centers per se, but we have used in other modeled products data from the Department of Energy which collects data on energy consumption. And detailed -- we use that for a project to estimate what proportion of household use air-conditioning, which is not asked in the ACS. So we brought in that particular data.
So the Department of Energy, we could probably have a look to see what kind of detailed sources and energy consumption are available. And yes, we do have third party sources -- just depending on the subject matter. The other administrative data that I was talking about that is used in the LEIA model is data collected from federal communications commission, FCC, that measures broadband internet availability for each county and down to the lot group level based on seeds that are advertised and the type of technology. So we have a lot of sources that we could potentially draw from.
And yes, we have from other agencies, and from commercial sources. Rafi do you want to add anything to that? Rafi, were you aware of any energy consumption sources that specifically look at data center consumption?
>> RAFI GOLDBERG: I am not am I think we would love to get our hands on this data if they were available somewhere.
Yeah, I was just going to speak a little bit to the second part of the question, right. And you know, just to add that in this session we have been talking about internet adoption and usage data, whereas the FCC, as Heather mentioned, is the entity that collects data on where broadband infrastructure is actually available.
So we do have that -- you know a whole other data source. And as Heather mentioned, that is actually one of the inputs into the experimental model for project LEIA.
>> MODERATOR: Thank you so much. Thank you for the question and thank you for the responds, colleagues. We have a question from an online participant. We will go to him next. And then, sir, we will take your question after the online participant.
So Robert. Please, the floor is yours.
>> QUESTION: Yeah, thank you. The presenters, my question is in Uganda I work for a small organisation called Youth and Technology and Development in Uganda. I've been listening, and down here we have the challenge of measures internet. I was wondering, do you offer capacity building training now to measure internet for organisations like mine if interested in such? Thank you.
>> So I will briefly chime. In that is a very excellent point we can take to our colleagues. We do think there are great things on this topic so more to come but we work closely with the US training inn duty so it's something to consider for future. I don't know if my colleagues online have anything to add.
>> MODERATOR: We also have provided email address on one of those slides. So please let us know if you do not have those email addresses and we can find a way to provide them to you. Thank you for the question. Sir. Please.
>> QUESTION: Thank you. Ron from the internet registry, that is also appraised the largest network of internet measurement devices so-called atlas props and atlas itself. So the question is about when do we talk about the access to the broadband infrastructure, are we also considering measuring the equal of this infrastructure? Because the access to it is not always the readiness of this infrastructure for the next level of digital economies, for the AI and the augmented reality and Metaverse, et cetera.
Do you also measure how do users use this internet? So is it used only for primal functions or used for the access to AI or Metaverse applications and activities? Do you think that there should be some measurement done to ensure -- and efforts based on that that should ensure the readiness of internet infrastructure for the next level of internet development and digital development. Thank you.
>> LUIS ZAMBRANO: I will take the first part of the question and pass it on to my colleagues. At least for us, it does measure some internet activities like internet usage and telework and the like. I think there are a range of activities online but we are always looking to improve and iterate upon the service instrument, that we can actually focus on the way people are using the internet today. And Rafi, I don't know if you have anything else to add to that.
>> RAFI GOLDBERG: Yeah, no, that is exactly right. And I would just add in terse of the sort of direct network measurement, you know, there have been efforts at the FCC as well as in the private sector with firms like UKLA and Microsoft and others to -- you know measure actual -- you know speeds and latency and other metrics related to the quality of the internet connection that folks actually experience. Which I agree is another very important piece of the puzzle.
So it's not -- you know one of our programmes, but I think another very important area for us, certainly.
>> QUESTION: Thank you. We are ready to share our resource as well and our knowledge for that. Thank you.
>> MODERATOR: Thank you. Let's exchange information. And we can be in touch after this session. Are there any other questions? Yes, sir. Please.
>> QUESTION: Thank you. I'm audible? Alright. This is Joshua Perry from Uganda (?) chapter am I have a question on desegregation. Do you do any desegregation to maybe -- like internet in schools? Because I think you seem to focus on households.
What about maybe in schools and in other institutions? Is that something you also measure? And how if you do. So thank you.
>> MODERATOR: Thank you. Glen question. May I turn to our colleagues in Washington.
>> RAFI GOLDBERG: Sure. Can I start. So these are household surveys which is why I think you have been hearing a lot about the households. We do in the NTIA internet use survey ask a range of questions about different locations of internet use. And one of those is internet use at school. So we do capture some information about that through this survey. I understand that there are other agencies throughout the government that also direction surveys toward the schools themselves.
And through that, right, if you are interested in learning more about how the school itself is use the internet, those would probably be the, you know, places to go for that information. But we do ask about internet use at school as well as using the internet for online courses or training as one of the many activities that we ask about as well.
>> MODERATOR: Excellent. Thank you. Anything to add on the census side?
>> LESLIE DAVIS: Thank you. Rafi is exactly right. On the census side it's how the questions are mandated. Questions are at a household level. But there are other sources I believe, within census as well on other surveys that get more at the school or how training are done at the school level.
>> LUIS ZAMBRANO: And one thing I want to plug in as one of Heather's slides. It's data.census.gov for access to various census data products.
>> MODERATOR: Thank you, just asking if we have any questions.
>> ONLINE MODERATOR: Nothing moron line.
>> MODERATOR: Any questions from the room? Please?
>> QUESTION: A quick one from international think tank perspective.
When we speak to member states, the trouble is not just data collection but actually using it for targeted initiatives for those who are not yet included or using the internet. So how does your data collection feed into the decision making process at county or state or central/federal government level to really make initiatives that targets those geographical segments and household user segments that have not yet got the access, got the skills or not yet using the internet for various functions, anything from participating in public discourse, using government services online, shopping online, banking online. How is your data collection feeding into that to really ensure that we get those who are excluded online and included? Thanks.
>> MODERATOR: Thank you for the question. We turn Torah if I. Would you be able to offer an answer to the question.
>> RAFI GOLDBERG: Yeah, I think I have heard from many state broadband offices in particular that -- you know they like to make use of our data when -- you know they are designing programmes to, you know serve their constituents. So certainly, you know, at the federal level we don't have a monopoly on how we use these data. Certainly state and local governments and nonprofits in the private sector make use of these data all the time for their own work.
You know, it is not uncommon for us here at NTIA and elsewhere in the government to site. So our data, for example, in an FCC filing, or -- you know in another venue where -- you know we are analyzing various policy issues.
So that, I think, is part of how this is helpful. But you know, we certainly don't think that we have a monopoly on how to best make use of the data. One very important feature of these datasets is they are all available for public use. And researchers and advocates on the outside do a lot of great things using our data.
>> MODERATOR: Thank you so much, Rafi. We just have a few minutes left am I would just like to invite the audience to share any of their experiences on measuring internet use. Please feel free. We did flag these questions towards the top of the session. But we still do have some time, if anybody would like to contribute.
>> QUESTION: Well, I can share a bit about our experience not about sharing internet or measuring internet use, but with the initiative that is called Internet Measurement Data that we do with ICAN, and we do it with different countries together. And just trying to show the country how to use the internet measure instruments to see what is their counter position on broadband security, and what is their position on the interconnection with the other countries and what is their condition about the -- inside the country.
So I guess we should have similar activities so we can have more under the circumstancing how we can improve the situation to have these networks already. Because we talk a lot about these digital services but there should also be the understanding to ensure the digital services to ensure this next level digital development we should have an appropriate level of internet development in the country. Appropriate level of critical, resilient infrastructures in the country, route servers, IXPs, all of stuff that is connected and that is equivalent to the needs of digital economy and society of the future of now. Because now is the future.
>> MODERATOR: Thank you. Thank you so much. We are wrapping up. And our time is concluding. So I just want to thank everybody for their contributions to this discussion. And Jaisha, may I turn it to you to conclude.
>> JAISHA WRAY: Sure. Again, thank you for participating. We appreciated the active discussion. It's clear there is a lot of interest in this topic. Our goal today was to introduce it. And to continue the discussion. So please feel free to reach out to us. Our virtual doors are open. And we looking forward to hearing from all of you and continuing to exchange lessons learned in this area and moving forward and exploring areas for cooperation as well. So again, thank you. And we will see you next time. Take care.
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