Dear Sophie: How can employers hire & comply with all this new H-1B craziness?

Here’s another edition of “Dear Sophie,” the advice column that answers immigration-related questions about working at technology companies.

“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”

Extra Crunch members receive access to weekly “Dear Sophie” columns; use promo code ALCORN to purchase a one or two-year subscription for 50% off.


Dear Sophie:

I’ve been reading about the new H-1B rules for wage levels and defining what types of jobs qualify that came out this week. What do we as employers need to do to comply? Are any other visa types affected?

— Racking my brain in Richmond! 🤯

Dear Racking:

As you mentioned, the Department of Labor (DOL) and the Department of Homeland Security (DHS) each issued a new interim rule this week that affects the H-1B program. However, the DOL rule impacts other visas and green cards as well. These interim rules, one of which took effect immediately after being published, are an abuse of power.

The president continues to fear-monger in an attempt to generate votes through racism, protectionism and xenophobia. The fatal irony here is that companies were in fact already making “real offers” to “real employees” for jobs in the innovation economy, which are not fungible and are actually the source of new job creation for Americans. A 2019 report by the Economic Policy Institute found that for every 100 professional, scientific and technical services jobs created in the private sector in the U.S., 418 additional, indirect jobs are created as a result. Nearly 575 additional jobs are created for every 100 information jobs, and 206 additional jobs are created for every 100 healthcare and social assistance jobs.

The DOL rule, which went into effect on October 8, 2020, significantly raises the wages employers must pay to the employees they sponsor for H-1B, H-1B1 and E-3 specialty occupation visas, H-2B visas for temporary non-agricultural workers, EB-2 advanced degree green cards, EB-2 exceptional ability green cards and EB-3 skilled worker green cards.

The new DHS rule, which further restricts H-1B visas, will go into effect on December 7, 2020. DHS will not apply the new rule to any pending or previously approved petitions. That means your company should renew your employees’ H-1B visas — if eligible — before that date.

The American Immigration Lawyers Association (AILA) has formed a task force to review the rules and help with litigation. Although both the DOL and DHS rules will likely be challenged, they will likely remain in effect for some time before any litigation has an impact. They are actively seeking plaintiffs, including employees, employers and representatives of membership organizations who will be hurt by the new rules.

These 3 factors are holding back podcast monetization

Podcast advertising growth is inhibited by three major factors:

  • Lack of macro distribution, consumption and audience data.
  • Current methods of conversion tracking.
  • Idea of a “playbook” for podcast performance marketing.

Because of these limiting factors, it’s currently more of an art than a science to piece disparate data from multiple sources, firms, agencies and advertisers, into a somewhat conclusive argument to brands as to why they should invest in podcast advertising.

1. Lack of macro distribution, consumption and audience data

There were several resources that released updates based on what they saw in terms of consumption when COVID-19 hit. Hosting platforms, publishers and third-party tracking platforms all put out their best guesses as to what was happening. Advertisers’ own podcast listening habits had been upended due to lockdowns; they wanted to know how broader changes in listening habits were affecting their campaigns. Were downloads going up, down or staying the same? What was happening with sports podcasts, without sports?


Read part 1 of this article, Podcast advertising has a business intelligence gap, on TechCrunch.


At Right Side Up, we receive and analyze all of the available research from major publishers (Stitcher, aCast), to major platforms (Megaphone) and third-party research firms (Podtrac, IAB, Edison Research). However, no single entity encompasses the entire space or provides the kind of interactive, off-the-shelf customizable SaaS product we’d prefer, and that digitally native marketers expect. Plus, there isn’t anything published in real-time; most sources publish once or twice annually.

So what did we do? We reached out to trusted publishers and partners to gather data around shifting consumption due to COVID-19 ourselves, and determined that, though there was a drop in downloads in the short term, it was neither as precipitous nor as enduring as some had feared. This was confirmed by some early reports available, but how were we to evidence our own piecewise sample with another? Moreover, how could you invest 6-7 figures of marketing dollars if you didn’t have the firsthand intelligence we gathered and our subject matter experts on deck to make constant adjustments to your approach?

We were able to piece together trends we’re seeing that point to increased download activity in recent months that surpass February/March heights. We’ve determined that the industry is back on track for growth with a less steep, but still growing, listenership trajectory. But even though more recent reports have been published, a longitudinal, objective resource has not yet emerged to show a majority of the industry’s journey through one of the most disruptive media environments in recent history.

There is a need for a new or existing entity to create cohesive data points; a third party that collects and reports listening across all major hosts and distribution points, or “podcatchers,” as they’re colloquially called. As a small example: Wouldn’t it be nice to objectively track seasonal listening of news/talk programming and schedule media planning and flighting around that? Or to know what the demographics of that audience look like compared to other verticals?

What percentage increase in efficiency and/or volume would you gain from your marketing efforts in the channel? Would that delta be profitable against paying a nominal or ongoing licensing or research fee for most brands?

These challenges aren’t just affecting advertisers. David Cohn, VP of Sales at Megaphone, agrees that “full transparency from the listening platforms would make our jobs easier, along with everyone else’s in the industry. We’d love to know how much of an episode is listened to, whether an ad is skipped, etc. Along the same lines, having a central source for [audience] measurement would be ideal — similar to what Nielsen has been for TV.” This would also enable us to understand cross-show ad frequency, another black box for advertisers and the industry at large.

Podcast advertising has a business intelligence gap

There are sizable, meaningful gaps in the knowledge collection and publication of podcast listening and engagement statistics. Coupled with still-developing advertising technology because of the distributed nature of the medium, this causes uncertainty in user consumption and ad exposure and impact. There is also a lot of misinformation and misconception about the challenges marketers face in these channels.

All of this compounds to delay ad revenue growth for creators, publishers and networks by inhibiting new and scaling advertising investment, resulting in lost opportunity among all parties invested in the channel. There’s a viable opportunity for a collective of industry professionals to collaborate on a solution for unified, free reporting, or a new business venture that collects and publishes more comprehensive data that ultimately promotes growth for podcast advertising.

Podcasts have always had challenges when it comes to the analytics behind distribution, consumption and conversion. For an industry projected to exceed $1 billion in ad spend in 2021, it’s impressive that it’s built on RSS: A stable, but decades-old technology that literally means really simple syndication. Native to the technology is a one-way data flow, which democratizes the medium from a publishing perspective and makes it easy for creators to share content, but difficult for advertisers trying to measure performance and figure out where to invest ad dollars. This is compounded by a fractured creator, server and distribution/endpoint environment unique to the medium.

Because podcasts lag other media channels in business intelligence, it’s still an underinvested channel relative to its ability to reach consumers and impact purchasing behavior.

For creators, podcasting has begun to normalize distribution analytics through a rising consolidation of hosts like Art19, Megaphone, Simplecast and influence from the IAB. For advertisers, though, consumption and conversion analytics still lag far behind. For the high-growth tech companies we work with, and as performance marketers ourselves, measuring the return on investment of our ad spend is paramount.

Because podcasts lag other media channels in business intelligence, it’s still an underinvested channel relative to its ability to reach consumers and impact purchasing behavior. This was evidenced when COVID-19 hit this year, as advertisers that were highly invested or highly interested in investing in podcast advertising asked a very basic question: “Is COVID-19, and its associated lifestyle shifts, affecting podcast listening? If so, how?”

The challenges of decentralized podcast ad data

We reached out to trusted partners to ask them for insights specific to their shows.

Nick Southwell-Keely, U.S. director of Sales & Brand Partnerships at Acast, said: “We’re seeing our highest listens ever even amid the pandemic. Across our portfolio, which includes more than 10,000 podcasts, our highest listening days in Acast history have occurred in [July].” Most partners provided similar anecdotes, but without centralized data, there was no one, singular firm to go to for an answer, nor one report to read that would cover 100% of the space. Almost more importantly, there is no third-party perspective to validate any of the anecdotal information shared with us.

Publishers, agencies and firms all scrambled to answer the question. Even still, months later, we don’t have a substantial and unifying update on exactly what, if anything, happened, or if it’s still happening, channel-wide. Rather, we’re still checking in across a wide swath of partners to identify and capitalize on microtrends. Contrast this to native digital channels like paid search and paid social, and connected, yet formerly “traditional” media (e.g., TV, CTV/OTT) that provide consolidated reports that marketers use to make decisions about their media investments.

The lasting murkiness surrounding podcast media behavior during COVID-19 is just one recent case study on the challenges of a decentralized (or nonexistent) universal research vendor/firm, and how it can affect advertisers’ bottom lines. A more common illustration of this would be an advertiser pulling out of ads, for fear of underdelivery on a flat rate unit, missing out on incremental growth because they were worried about not being able to get download reporting and getting what they paid for. It’s these kinds of basic shortcomings that the ad industry needs to account for before we can hit and exceed the ad revenue heights projected for podcasting.

Advertisers may pull out of campaigns for fear of under-delivery, missing out on incremental growth because they were worried about not getting what they paid for.

If there’s a silver lining to the uncertainty in podcast advertising metrics and intelligence, it’s that supersavvy growth marketers have embraced the nascent medium and allowed it to do what it does best: personalized endorsements that drive conversions. While increased data will increase demand and corresponding ad premiums, for now, podcast advertising “veterans” are enjoying the relatively low profile of the space.

As Ariana Martin, senior manager, Offline Growth Marketing at Babbel notes, “On the other hand, podcast marketing, through host read ads, has something personal to it, which might change over time and across different podcasts. Because of this personal element, I am not sure if podcast marketing can ever be transformed into a pure data game. Once you get past the understanding that there is limited data in podcasting, it is actually very freeing as long as you’re seeing a certain baseline of good results, [such as] sales attributed to podcast [advertising] via [survey based methodology], for example.”

So how do we grow from the industry feeling like a secret game-changing channel for a select few brands, to widespread adoption across categories and industries?

Below, we’ve laid out the challenges of nonuniversal data within the podcast space, and how that hurts advertisers, publishers, third-party research/tracking organizations, and broadly speaking, the podcast ecosystem. We’ve also outlined the steps we’re taking to make incremental solutions, and our vision for the industry moving forward.

Lingering misconceptions about podcast measurement

1. Download standardization

In search of a rationale to how such a buzzworthy growth channel lags behind more established media types’ advertising revenue, many articles will point to “listener” or “download” numbers not being normalized. As far as we can tell at Right Side Up, where we power most of the scaled programs run by direct advertisers, making us a top three DR buying force in the industry, the majority of publishers have adopted the IAB Podcast Measurement Technical Guidelines Version 2.0.

This widespread adoption solved the “apples to apples” problem as it pertained to different networks/shows valuing a variable, nonstandard “download” as an underlying component to their CPM calculations. Previous to this widespread adoption, it simply wasn’t known whether a “download” from publisher X was equal to a “download” from publisher Y, making it difficult to aim for a particular CPM as a forecasting tool for performance marketing success.

However, the IAB 2.0 guidelines don’t completely solve the unique-user identification problem, as Dave Zohrob, CEO of Chartable points out. “Having some sort of anonymized user identifier to better calculate audience size would be fantastic —  the IAB guidelines offer a good approximation given the data we have but [it] would be great to actually know how many listeners are behind each IP/user-agent combo.”

2. Proof of ad delivery

A second area of business intelligence gaps that many articles point to as a cause of inhibited growth is a lack of “proof of delivery.” Ad impressions are unverifiable, and the channel doesn’t have post logs, so for podcast advertisers the analogous evidence of spots running is access to “airchecks,” or audio clippings of the podcast ads themselves.

Legacy podcast advertisers remember when a full-time team of entry-level staffers would hassle networks via phone or email for airchecks, sometimes not receiving verification that the spot had run until a week or more after the fact. This delay in the ability to accurately report spend hampered fast-moving performance marketers and gave the illusion of podcasts being a slow, stiff, immovable media type.

Systematic aircheck collection has been a huge advent and allowed for an increase in confidence in the space — not only for spend verification, but also for creative compliance and optimization. Interestingly, this feature has come up almost as a byproduct of other development, as the companies who offer these services actually have different core business focuses: Magellan AI, our preferred partner, is primarily a competitive intelligence platform, but pivoted to also offer airchecking services after realizing what a pain point it was for advertisers; Veritone, an AI company that’s tied this service to its ad agency, Veritone One; and Podsights, a pixel-based attribution modeling solution.

3. Competitive intelligence

Last, competitive intelligence and media research continue to be a challenge. Magellan AI and Podsights offer a variety of fee and free tiers and methods of reporting to show a subset of the industry’s activity. You can search a show, advertiser or category, and get a less-than-whole, but still directionally useful, picture of relevant podcast advertising activity. While not perfect, there are sufficient resources to at least see the tip of the industry iceberg as a consideration point to your business decision to enter podcasts or not.

As Sean Creeley, founder of Podsights, aptly points out: “We give all Podsights research data, analysis, posts, etc. away for free because we want to help grow the space. If [a brand], as a DIY advertiser, desired to enter podcasting, it’s a downright daunting task. Research at least lets them understand what similar companies in their space are doing.”

There is also a nontech tool that publishers would find valuable. When we asked Shira Atkins, co-founder of Wonder Media Network, how she approaches research in the space, she had a not-at-all-surprising, but very refreshing response: “To be totally honest, the ‘research’ I do is texting and calling the 3-5 really smart sales people I know and love in the space. The folks who were doing radio sales when I was still in high school, and the podcast people who recognize the messiness of it all, but have been successful at scaling campaigns that work for both the publisher and the advertiser. I wish there was a true tracker of cross-industry inventory — how much is sold versus unsold. The way I track the space writ large is by listening to a sample set of shows from top publishers to get a sense for how they’re selling and what their ads are like.”

Even though podcast advertising is no longer limited by download standardization, spend verification and competitive research, there are still hurdles that the channel has not yet overcome.


The conclusion to this article, These 3 factors are holding back podcast monetization, is available exclusively to Extra Crunch subscribers.

Enhanced computer vision, sensors raise manufacturing stakes for robots as a service

For more than two decades, robotics market commentaries have predicted a shift, particularly in manufacturing, from traditional industrial manipulators to a new generation of mobile, sensing robots, called “cobots.” Cobots are agile assistants that use internal sensors and AI processing to operate tools or manipulate components in a shared workspace, while maintaining safety.

It hasn’t happened. Companies have successfully deployed cobots, but the rate of adoption is lagging behind expectations.

According to the International Federation of Robotics (IFR), cobots sold in 2019 made up just 3% of the total industrial robots installed. A report published by Statista projects that in 2022, cobots’ market share will advance to 8.5%. This is a fraction of a February 2018 study cited by the Robotic Industries Association that forecasted by 2025, 34% of the new robots being sold in the U.S. will be cobots.

To see a cobot in action, here’s the Kuka LBR iiwa. To ensure safe operation, cobots come with built-in constraints, like limited strength and speed. Those limitations have also limited their adoption.

As cobots’ market share languishes, standard industrial robots are being retrofitted with computer vision technology, allowing for collaborative work combining the speed and strength of industrial robots with the problem-solving skills and finesse of humans.

This article will document the declining interest in cobots, the reasons for it and the technology that is replacing it. We report on two firms developing computer vision technology for standard robots and describe how developments in 3D vision and so-called “robots as a service” (yes, RaaS) are defining this faster-growing second generation of robots that can work alongside humans.

What are robotics sensing platforms?

Dear Sophie: Is it easier and faster to get an O-1A than an EB-1A?

Here’s another edition of “Dear Sophie,” the advice column that answers immigration-related questions about working at technology companies.

“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”

“Dear Sophie” columns are accessible for Extra Crunch subscribers; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.


Dear Sophie:

Is it easier and faster to get an O-1A extraordinary ability visa than an EB-1A extraordinary ability green card? What are the pros and cons of each?

—Outstanding in Oakland

Dear Outstanding:

Thanks so much for your timely questions about the extraordinary ability visa and green card. The short answer to your first question is yes, the O-1A visa is generally easier and faster to get than an EB-1A green card. In fact, I once helped a client get an O-1A approved in three days — of course, that was before the COVID-19 pandemic.

We recently launched “Extraordinary Ability Bootcamp,” a new, 15-module online course that takes a deep dive into the O-1A extraordinary ability nonimmigrant (temporary) visa, the EB-1A extraordinary ability green card, the EB-2 NIW (National Interest Waiver for exceptional ability) and what it takes to file a successful application in each category. Check my podcast where I discuss the Bootcamp in more detail. Register for the Extraordinary Ability Bootcamp and use code DEARSOPHIE for 20% off the enrollment fee.

In general, the requirements for a green card, which enable its holder to live permanently in the U.S., are more stringent than those for nonimmigrant visas, which only allow a temporary stay in the U.S. And U.S. Citizenship and Immigration Services (USCIS) typically takes longer to process green card petitions than nonimmigrant visa petitions. Moreover, the U.S. imposes numerical and per-country caps on the number of green cards issued each year, which means some green card categories for people born in some countries, such as India and China, face long waits. Only a few visas have an annual cap (like the H-1B), but the O-1A visa is not one of them.

That said, the EB-1A has one of the shortest USCIS processing times, compared to other employment-based green cards. Also, EB-1A petitions are eligible for premium processing, which requires USCIS to make a decision on a petition within 15 days (whether it is “calendar” days or “business” days is currently in flux!). The I-140 petition can be adjudicated quickly in a few weeks, but for somebody whose priority date is “current” on the Visa Bulletin, the determining factor for how long a green card takes is often the I-485 processing time in the local field office. Recently that’s been taking about 1.5-2 years for interviews in the Bay Area.

Meanwhile, nonimmigration visa petitions can face delays for a number of reasons, but a delay happens most often when USCIS responds to a petition with a Request for Evidence (RFE). An RFE is a written notice from USCIS seeking additional evidence to make a decision on a case. During the past few years, the number of RFEs issued by USCIS for both visas and green cards has increased substantially.

Last month (September 2020) USCIS extended its policy of giving petitioners an extra 60 calendar days to respond to certain USCIS notices, including RFEs, intent to deny, revoke, rescind and terminate due to the ongoing coronavirus pandemic. For any of these notices dated between March 1, 2020, and January 1, 2021, a timely response will be considered 60 days after the date listed on the notice. Whether you want to take advantage of this extra time is a conversation to have with your attorney, based on the strength of your pending petition and the urgency of getting an approval.

As you probably know, the O-1A visa is for individuals who have achieved national or international acclaim and have risen to the top of their field in the areas of science, education, business or athletics. The EB-1A enables individuals who have achieved substantial international or national success in their field due to their extraordinary talent to live permanently in the U.S.

Here’s a summary of the pros and cons of the O-1A and the EB-1A:

O-1A NONIMMIGRANT VISA

(Temporary Stay)

EB-1A GREEN CARD

(Permanent Residence)

Pros

  • Easier standard than EB-1A.
  • A change of status can be processed by USCIS in a few weeks.
  • Eligible for premium processing.
  • Unlimited extensions possible.
  • Does not require an LCA or PERM.
  • No annual cap.
Pros

  • Possible to self-petition without an employer sponsor or job offer.
  • I-140 is eligible for premium processing.
  • Green card: Allows you to permanently remain in the U.S.
  • Does not require an LCA or PERM.
  • Five years after green card can apply for citizenship.
Cons

  • Requires employer or agent sponsorship.
  • Requires job offer or itinerary of gigs.
  • Individuals cannot self-petition.
  • Might require union letter or advisory opinion.
  • Not a green card (permanent residence).
Cons

  • Multiyear process.
  • High evidentiary standard.
  • Annual numerical and per-country caps exist.
  • Backlog for people born in India and China.
  • Under a presidential proclamation issued in April, green cards not currently being issued at Consulates.

Keep in mind that like the EB-1, the EB-2 NIW (National Interest Waiver) green card does not require an employer sponsor. However, the eligibility requirements for the EB-2 NIW are less stringent than for the EB-1A. For individuals born in India and China, the downside to the EB-2 NIW green card is that they face a much longer wait compared to the EB-1A. Unlike the EB-1A, premium processing is not available for EB-2 NIW petitions.

Remember, U.S. embassies and consulates are not processing green cards so you should try to apply for a green card while you remain in legal status in the U.S. Otherwise, you may have to return to and stay in your home country for a while.

Still, getting a visa or green card abroad remains possible. I recommend working with an experienced immigration attorney to discuss which options best match your accomplishments, goals and timing. Remember, you can sign up for Bootcamp and use code DEARSOPHIE for 20% off the enrollment fee to get qualified!

All my best,

Sophie


Have a question? Ask it here. We reserve the right to edit your submission for clarity and/or space. The information provided in “Dear Sophie” is general information and not legal advice. For more information on the limitations of “Dear Sophie,” please view our full disclaimer here. You can contact Sophie directly at Alcorn Immigration Law.

Sophie’s podcast, Immigration Law for Tech Startups, is available on all major podcast platforms. If you’d like to be a guest, she’s accepting applications!

Standing by developers through Google v. Oracle

The Supreme Court will hear arguments tomorrow in Google v. Oracle. This case raises a fundamental question for software developers and the open-source community: Whether copyright may prevent developers from using software’s functional interfaces — known as APIs — to advance innovation in software. The court should say no — free and open APIs protect innovation, competition and job mobility for software developers in America.

When we use an interface, we don’t need to understand (or care) about how the function on the other side of the interface is performed. It just works. When you sit down at your computer, the QWERTY keyboard allows you to rapidly put words on the screen. When you submit an online payment to a vendor, you are certain the funds will appear in the vendor’s account. It just works.

In the software world, interfaces between software programs are called “application programming interfaces” or APIs. APIs date back to the 1950s and allow developers to write programs that reuse other program functionality without knowing how that functionality is performed. If your program needs to sort a list, you could have it use a sorting program’s API to sort the list for your program. It just works.

Developers have historically used software interfaces free of copyright concerns, and this freedom has accelerated innovation, software interoperation and developer job mobility. Developers using existing APIs save time and effort, allowing those savings to be refocused on new ideas. Developers can also reimplement APIs from one software platform to others, enabling innovation to flow freely across software platforms.

Importantly, reusing APIs gives developers job portability, since knowledge of one set of APIs is more applicable cross-industry. The upcoming Google v. Oracle decision could change this, harming developers, open-source software and the entire software industry.

Google v. Oracle and the platform API bargain

Google v. Oracle is the culmination of a decade-long dispute. Back in 2010, Oracle sued Google, arguing that Google’s Android operating system infringed Oracle’s rights in Java. After ten years, the dispute now boils down to whether Google’s reuse of Java APIs in Android was copyright infringement.

Prior to this case, most everyone assumed that copyright did not cover the use of functional software like APIs. Under that assumption, competing platforms’ API reimplementation allowed developers to build new yet familiar things according to the API bargain: Everyone could use the API to build applications and platforms that interoperate with each other. Adhering to the API made things “just work.”

But if the Google v. Oracle decision indicates that API reimplementation requires copyright permission, the bargain falls apart. Nothing “just works” unless platform makers say so; they now dictate rules for interoperability — charging developers huge prices for the platform or stopping rival, compatible platforms from being built.

Free and open APIs are essential for modern developers

If APIs are not free and open, platform creators can stop competing platforms from using compatible APIs. This lack of competition blocks platform innovation and harms developers who cannot as easily transfer their skills from project to project, job to job.

MySQL, Oracle’s popular database, reimplemented mSQL’s APIs so third-party applications for mSQL could be “ported easily” to MySQL. If copyright had restricted reimplementation of those APIs, adoption of MySQL, reusability of old mSQL programs and the expansion achieved by the “LAMP” stack would have been stifled, and the whole ecosystem would be poorer for it. This and other examples of API reimplementation — IBM’s BIOS, Windows and WINE, UNIX and Linux, Windows and WSL, .NET and Mono, have driven perhaps the most amazing innovation in human history, with open-source software becoming critical digital infrastructure for the world.

Similarly, a copyright block on API-compatible implementations puts developers at the mercy of platform makers say so — both for their skills and their programs. Once a program is written for a given set of APIs, that program is locked-in to the platform unless those APIs can also be used on other software platforms. And once a developer learns skills for how to use a given API, it’s much easier to reuse than retrain on APIs for another platform. If the platform creator decides to charge outrageous fees, or end platform support, the developer is stuck. For nondevelopers, imagine this: The QWERTY layout is copyrighted and the copyright owner decided to charge $1,000 dollars per keyboard. You would have a choice: Retrain your hands or pay up.

All software used by anyone was created by developers. We should give developers the right to freely reimplement APIs, as developer ability to shift applications and skills between software ecosystems benefits everyone — we all get better software to accomplish more.

I hope that the Supreme Court’s decision will pay heed to what developer experience has shown: Free and open APIs promote freedom, competition, innovation and collaboration in tech.

Dear Sophie: Now that a judge has paused Trump’s H-1B visa ban, how can I qualify my employees?

On Thursday, October 1, a federal judge issued a temporary injunction that halted a presidential proclamation issued in June suspending the issuance of visas for some foreign workers until at least December 31, 2020.

The Trump administration asserted that the COVID-19 pandemic and its ensuing economic impacts made it necessary to impose a moratorium on issuing new green cards, but Judge Jeffrey S. White of the U.S. District Court for the Northern District of California ruled that:

There must be some measure of constraint on Presidential authority in the domestic sphere in order not to render the executive an entirely monarchical power in the immigration context, an area within clear legislative prerogative …

To explain how employers can respond to the judge’s order, TechCrunch columnist and Silicon Valley-based immigration lawyer Sophie Alcorn has written a supplemental column.

Extra Crunch members receive access to weekly “Dear Sophie” columns; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.


Dear Sophie:

I just saw yesterday’s news that a judge issued a temporary injunction on the presidential proclamation that halted the issuance of H, L and J visas for individuals abroad, but that it only protects companies in the plaintiff organizations. We have several new hires waiting for visa interviews outside of the U.S. How can they now qualify to get visas to come to the U.S.?

— Supercharged in Sunnyvale

Dear Supercharged:

I’m thrilled that Judge Jeffrey S. White of the U.S. District Court for the Northern District of California temporarily halted President Trump’s June proclamation, which suspended the issuance of H, J, L and other temporary work visas to individuals abroad.

Judge White found that Trump overstepped his authority and exercised “monarchical power” by barring these work visas, adding that it’s in the public interest to uphold the power of Congress in determining immigration matters. The executive proclamation “completely disregards both the economic reality and the preexisting statutory framework,” the judge wrote, “without any consideration of the impact on American firms and their business planning.”

The judge issued his order in response to a lawsuit filed in July by business groups against the Department of Homeland Security and the State Department. The suit challenged the legality of the June proclamation, which suspended the issuance of H-1B and other temporary work visas — and corresponding dependent visas — at U.S. embassies and consulates.

The order requires U.S. Citizenship and Immigration Services (USCIS), an agency within Homeland Security, and the State Department to resume processing and issuing the following visas to the plaintiff organizations that brought the lawsuit:

  • H-1B visas for specialty occupations, which means if you have an approved H-1B petition from the March 2020 H-1B visa lottery, your H-1B visa beneficiary could proceed for an interview consular processing.
  • H-2B visas for temporary nonagricultural workers.
  • H-4 visas for the dependent spouse and children of H-1B and H-2B visa holders.
  • J-1 visas for interns, trainees, teachers, camp counselors, au pairs or the summer work travel program.
  • J-2 visas for the dependent spouse and children of J-1 visa holders.
  • L-1 visas and Blanket L petitions for managers and executives or specialized knowledge workers.
  • L-2 visas for the spouse and children of L-1 visa holders.

However, the preliminary injunction only applies to members of the plaintiff organizations. Therefore, it may be prudent for your company to seek membership in one of the following plaintiff organizations, such as the U.S. Chamber of Commerce, in order to seek inclusion in the protected group to qualify for visa interviews for your employees:

Judge White’s preliminary injunction remains in effect until a final ruling in the case — or an appeal of the case. An appeal appears likely given that last month in a separate case, Judge Amit P. Mehta of the U.S. District Court of the District of Columbia declined to halt both the June proclamation and one issued in April barring green card applicants from entering the U.S.

Also last week, another piece of welcome news affecting immigration came from Judge White: In a separate case, he blocked USCIS’s new fee rule that was slated to go into effect on Oct. 2, 2020. The new rule would have dramatically increased the fees for applying for many immigration and naturalization benefits, including visa and green card petitions.

I’m glad to hear that your visa candidates, particularly for H-1B visas, are only awaiting visa interviews at a U.S. embassy or consulate. That’s because USCIS is expected to issue a new rule shortly that is designed to further restrict the issuance of H-1B visas. The new rule is expected to narrow which jobs qualify for an H-1B specialty occupation visa, limit or even exclude H-1B beneficiaries working at a third-party worksite, and significantly increase the minimum wage rate for H-1B recipients.

Remember that travel restrictions remain in place that bar foreign nationals who have been in any of the following countries during the past 14 days from entering the U.S.:

  • China
  • Iran
  • The European Schengen areas of Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Monaco, San Marino and Vatican City
  • United Kingdom
  • Republic of Ireland
  • Brazil

We often recommend that any new hires consider traveling to a country not on this list for at least a 14-day layover before proceeding to the U.S.

Congrats and best wishes!

Sophie


Adding to the recent string of good news in immigration, the Department of Labor’s Office of Foreign Labor Certification (OFLC) recently announced it will now issue PERM labor certifications electronically to employers, which should result in faster notifications. Employers must file for a PERM labor certification if they sponsor an employee for either an EB-2 or an EB-3 green card. The OFLC must approve a PERM application before an employer can submit an EB-2 or EB-3 green card petition to USCIS.


Have a question? Ask it here. We reserve the right to edit your submission for clarity and/or space. The information provided in “Dear Sophie” is general information and not legal advice. For more information on the limitations of “Dear Sophie,” please view our full disclaimer here. You can contact Sophie directly at Alcorn Immigration Law.

Sophie’s podcast, Immigration Law for Tech Startups, is available on all major podcast platforms. If you’d like to be a guest, she’s accepting applications!

 

Which neobanks will rise or fall?

The neobank, or digital bank, phenomenon continues to take the world by storm, with global winners, from Brazil’s Nubank valued at $10 billion and Berlin’s N26 valued at $3.5 billion, to Chime, now valued at $14.5 billion as the most valuable consumer fintech in the United States.

Neobanks have led the charge of the $3.6 billion in venture capital funding for consumer fintech startups this year. And as the coronavirus-fueled acceleration of digital transformation continues, it seems the digital bank is here to stay, with some estimates pointing to neobanks reaching 60 million customers in North America and Europe by the end of 2020, and surpassing 145 million by 2024.

The space is also becoming more crowded, a trend which will only accelerate with fintech eating the world and creating greater infrastructure that enables any company to include a bank account as a product extension.

As a result, neobanks are not a monolithic model and not all are created equal. Looking underneath the hood of business models across the globe reveals remarkable operational differences and highlights specific features that are more likely to succeed in the long-term.

Five global models of neobanks

Today there are five distinct models that are leading globally:

Interchange-led: Relies on payments revenue, sourced through interchange as the revenue driver. Every time a customer uses the neobank’s card as a payment method they get paid [e.g. Chime / US; Neon (hybrid of 1 & 2) / Brazil].

Credit-led: Leverages a credit-first model, starting off with a credit card or similar offering, and later providing a bank account [e.g. Nubank, Neon (hybrid of 1 & 2) / Brazil].

There’s a way to pick the absolute best images for your content: Apply AI

Most marketers believe there’s a lot of value in having relevant, engaging images featured in content.

But selecting the “right” images for blog posts, social media posts or video thumbnails has historically been a subjective process. Social media and SEO gurus have a slew of advice on picking the right images, but this advice typically lacks real empirical data.

This got me thinking: Is there a data-driven — or even better, an AI-driven — process for gaining deeper insight into which images are more likely to perform well (aka more likely to garner human attention and sharing behavior)?

The technique for finding optimal photos

In July of 2019, a fascinating new machine learning paper called “Intrinsic Image Popularity Assessment” was published. This new model has found a reliable way to predict an image’s likely “popularity” (estimation of likelihood the image will get a like on Instagram).

It also showed an ability to outperform humans, with a 76.65% accuracy on predicting how many likes an Instagram photo would garner versus a human accuracy of 72.40%.

I used the model and source code from this paper to come up with how marketers can improve their chances of selecting images that will have the best impact on their content.

Finding the best screen caps to use for a video

One of the most important aspects of video optimization is the choice of the video’s thumbnail.

According to Google, 90% of the top performing videos on the platform use a custom selected image. Click-through rates, and ultimately view counts, can be greatly influenced by how eye-catching a video title and thumbnail are to a searcher,

In recent years, Google has applied AI to automate video thumbnail extraction, attempting to help users find thumbnails from their videos that are more likely to attract attention and click-throughs.

Unfortunately, with only three provided options to choose from, it’s unlikely the thumbnails Google currently recommends are the best thumbnails for any given video.

That’s where AI comes in.

With some simple code, it’s possible to run the “intrinsic popularity score” (as derived by a model similar to the one discussed in this article) against all of the individual frames of a video, providing a much wider range of options.

The code to do this is available here. This script downloads a YouTube video, splits it into frames as .jpg images, and runs the model on each image, providing a predicted popularity score for each frame image.
Caveat: It is important to remember that this model was trained and tested on Instagram images. Given the similarity in behavior for clicking on an Instagram photo or a YouTube thumbnail, we feel it’s likely (though never tested) that if a thumbnail is predicted to do well as an Instagram photo, it will similarly do well as a YouTube video thumbnail.

Let’s look at an example of how this works.

 

thumbnail from youtube video with housebuilding couple

Current thumbnail. Image Credits: YouTube (opens in a new window)

 

We had the intrinsic popularity model look at three frames per second of this 23-minute video. It took about 20 minutes. The following were my favorites from the 20 images that had the highest overall scores.

Latin America’s digital transformation is making up for lost time

“Gradually, then suddenly.” Hemingway’s words succinctly capture the recent history of tech in Latin America. After more than a decade of gradual progress made through fits and starts, tech in Latin America finally hit its stride and has been growing at an accelerating pace in recent years.

The region now boasts 17 unicorns up from zero just three years ago. For the first time, the most valuable company in the region isn’t a state-controlled oil or mining behemoth, but rather e-commerce platform MercadoLibre.

We are only in the first chapter of this long story, however. When we compare the penetration of tech companies in Latin America to both developed and developing markets, we estimate that the market could grow nearly tenfold over the next decade. The value to be unlocked will be measured in trillions of dollars and the lives improved in the hundreds of millions.

Our venture capital fund, Atlantico, conducts a thorough annual analysis of market data from Latin America in what we call the Latin America Digital Transformation Report. The report consists of hundreds of data-rich slides based off of original studies, surveys and models constructed from a combination of public and proprietary data shared by many of the region’s leading tech companies. This year, for the first time, we have decided to make the report public and here we highlight some of the findings from this year.

Global venture capitalists, the likes of Sequoia, Benchmark and a16z have planted their flags through key investments in companies like Nubank, Wildlife and Loft. Those are not isolated incidents – venture capital investments in the region have nearly doubled annually for the last three years according to the Latin American Venture Capital Association (LAVCA). In order to understand what investors are seeing in the region, we analyzed the market through a simple framework we apply throughout our report.

The starting point for this framework is the socioeconomic foundation in place. The context in which transformation occurs is important in shaping its possible outcome. The same ingredients applied in different contexts and time periods will produce very different results. Thus, we believe that Latin America is unique globally, and the types of companies that will flourish (and to what extent) will be different than in other parts of the world. Trying to shoehorn foreign business models and products is unlikely to yield good results.

In the case of Latin America, it’s key to remember the region boasts a population twice that of the United States and a GDP half that of China’s (but similar on a per capita basis). In short: Latin America is big, a central factor that has the power to attract capital and talent. However, also critical to note is that economic inequality is severe. While a quarter of the region’s population lives in poverty, the wealthy in Mexico City and São Paulo enjoy living standards in line with their peers in New York and London.

This unique mix of large opportunity and critical problems waiting to be solved has provided fertile ground for the gig economy to flourish. Case-in-point: Brazil is Uber’s largest market globally in volume of rides, with São Paulo its largest city. Rappi, a major food delivery player in the region, valued at over $3 billion, grew its sales by 113% over the first five months of the pandemic. When taken together, the largest ride-hailing and food-delivery services in Brazil are already the largest private employer in Brazil, a formidable contribution to reducing high unemployment.

When we track technology company value as a percent of the economy (tech company market cap as a % of GDP) we clearly see that Latin America, at 2.2% penetration, has a ways to go. Our estimate is that it is 10 years behind China (at 27% penetration), which itself is five years behind current U.S. levels (39% penetration).

Image Credits: Atlantico

However, it is important to note that Latin America is making up for lost time. This metric for tech company penetration or share has been growing on average at 65% per year since 2003. In comparison, the growth in U.S. tech company penetration has grown at 11% annually in the same period, while China’s has expanded at 40%.

https://www.atlantico.vc/latin-america-digital-transformation-report

Image Credits: Atlantico

Drivers of digital transformation

Within the socioeconomic context of the region, we advance to looking at the three drivers of change in our framework: people, capital and regulation.

On the people front, the greater visibility of successful role models has catalyzed a desire to follow entrepreneurial footsteps. People like Mike Krieger (co-founder of Instagram), Marcos Galperin (founder/CEO of Mercado Libre) and Henrique Dubugras (founder/co-CEO of Brex) have shown that local talent can go on to build global companies.

In a survey we conducted with nearly 1,700 college students from the top universities in Brazil, 26% of students voiced a desire to work at startups or big tech companies. A whopping 39% expressed plans to start a company in the future, that number rising to 60% when we consider only computer science students. As more and more of the region’s top graduates flock to tech, it gives us confidence in the accelerating growth of the sector over many years to come.

On the capital front, the growth of venture funding in the region has been frequently written about. Last year, it hit a peak of $4.6 billion after doubling from the year before. However, what perhaps is more surprising is that despite this rapid growth, we are still far from the ceiling. When we view venture capital investments as a proportion of GDP, we see Latin America as only one-seventh of the U.S. level and a quarter of the level in India.