4 things to remember when adapting AI/ML learning models during a pandemic

The machine learning and AI-powered tools being deployed in response to COVID-19 arguably improve certain human activities and provide essential insights needed to make certain personal or professional decisions; however, they also highlight a few pervasive challenges faced by both machines and the humans that create them.

Nevertheless, the progress seen in AI/machine learning leading up to and during the COVID-19 pandemic cannot be ignored. This global economic and public health crisis brings with it a unique opportunity for updates and innovation in modeling, so long as certain underlying principles are followed.

Here are four industry truths (note: this is not an exhaustive list) my colleagues and I have found that matter in any design climate, but especially during a global pandemic climate.

Some success can be attributed to chance, rather than reasoning

When a big group of people is collectively working on a problem, success may become more likely. Looking at historic examples like the 2008 Global Financial Crisis, there were several analysts credited with predicting the crisis. This may seem miraculous to some until you consider that more than 200,000 people were working in Wall Street, each of them making their own predictions. It then becomes less of a miracle and more of a statistically probable outcome. With this many individuals simultaneously working on modeling and predictions, it was highly likely someone would get it right by chance.

Similarly, with COVID-19 there are a lot of people involved, from statistical modelers and data scientists to vaccine specialists, and there is also an overwhelming eagerness to find solutions and concrete data-based answers. Following appropriate statistical rigor, coupled with machine learning and AI, can improve these models and decrease the chances of false predictions that arrive from too many predictions being made.

Automation can help in maintaining productivity if used wisely

During a crisis, time-management is essential. Automation technology can be used not only as part of the crisis solution, but also as a tool for monitoring productivity and contributions of team members working on the solution. For modeling, automation can also greatly improve the speed of results. Every second a piece of software can perform automation for a model, it allows a data scientist (or even a medical scientist) to conduct other more important tasks. User-friendly platforms in the market now give more people, like business analysts, access to predictions from custom machine learning models.

Privacy data management innovations reduce risk, create new revenue channels

Privacy data mismanagement is a lurking liability within every commercial enterprise. The very definition of privacy data is evolving over time and has been broadened to include information concerning an individual’s health, wealth, college grades, geolocation and web surfing behaviors. Regulations are proliferating at state, national and international levels that seek to define privacy data and establish controls governing its maintenance and use.

Existing regulations are relatively new and are being translated into operational business practices through a series of judicial challenges that are currently in progress, adding to the confusion regarding proper data handling procedures. In this confusing and sometimes chaotic environment, the privacy risks faced by almost every corporation are frequently ambiguous, constantly changing and continually expanding.

Conventional information security (infosec) tools are designed to prevent the inadvertent loss or intentional theft of sensitive information. They are not sufficient to prevent the mismanagement of privacy data. Privacy safeguards not only need to prevent loss or theft but they must also prevent the inappropriate exposure or unauthorized usage of such data, even when no loss or breach has occurred. A new generation of infosec tools is needed to address the unique risks associated with the management of privacy data.

The first wave of innovation

A variety of privacy-focused security tools emerged over the past few years, triggered in part by the introduction of GDPR (General Data Protection Regulation) within the European Union in 2018. New capabilities introduced by this first wave of innovation were focused in the following three areas:

Data discovery, classification and cataloging. Modern enterprises collect a wide variety of personal information from customers, business partners and employees at different times for different purposes with different IT systems. This data is frequently disseminated throughout a company’s application portfolio via APIs, collaboration tools, automation bots and wholesale replication. Maintaining an accurate catalog of the location of such data is a major challenge and a perpetual activity. BigID, DataGuise and Integris Software have gained prominence as popular solutions for data discovery. Collibra and Alation are leaders in providing complementary capabilities for data cataloging.

Consent management. Individuals are commonly presented with privacy statements describing the intended use and safeguards that will be employed in handling the personal data they supply to corporations. They consent to these statements — either explicitly or implicitly — at the time such data is initially collected. Osano, Transcend.io and DataGrail.io specialize in the management of consent agreements and the enforcement of their terms. These tools enable individuals to exercise their consensual data rights, such as the right to view, edit or delete personal information they’ve provided in the past.

Want to hire and retain high-quality developers? Give them stimulating work

Software developers are some of the most in-demand workers on the planet. Not only that, they’re complex creatures with unique demands in terms of how they define job fulfillment. With demand for developers on the rise (the number of jobs in the field is expected to grow by 22% over the next decade), companies are under pressure to do everything they can to attract and retain talent.

First and foremost — above salary — employers must ensure that product teams are made up of developers who feel creatively stimulated and intellectually challenged. Without work that they feel passionate about, high-quality programmers won’t just become bored and potentially seek opportunities elsewhere, the standard of work will inevitably drop. In one survey, 68% of developers said learning new things is the most important element of a job.

The worst thing for a developer to discover about a new job is that they’re the most experienced person in the room and there’s little room for their own growth.

Yet with only 32% of developers feeling “very satisfied” with their jobs, there’s scope for you to position yourself as a company that prioritizes the development of its developers, and attract and retain top talent. So, how exactly can you ensure that your team stays stimulated and creatively engaged?

Allow time for personal projects

78% of developers see coding as a hobby — and the best developers are the ones who have a true passion for software development, in and out of the workplace. This means they often have their own personal passions within the space, be it working with specific languages or platforms, or building certain kinds of applications.

Back in their 2004 IPO letter, Google founders Sergey Brin and Larry Page wrote:

We encourage our employees, in addition to their regular projects, to spend 20% of their time working on what they think will most benefit Google. [This] empowers them to be more creative and innovative. Many of our significant advances have happened in this manner.

At DevSquad, we’ve adopted a similar approach. We have an “open Friday” policy where developers are able to learn and enhance their skills through personal projects. As long as the skills being gained contribute to work we are doing in other areas, the developers can devote that time to whatever they please, whether that’s contributing to open-source projects or building a personal product. In fact, 65% of professional developers on Stack Overflow contribute to open-source projects once a year or more, so it’s likely that this is a keen interest within your development team too.

Not only does this provide a creative outlet for developers, the company also gains from the continuously expanding skillset that comes as a result.

Provide opportunities to learn and teach

One of the most demotivating things for software developers is work that’s either too difficult or too easy. Too easy, and developers get bored; too hard, and morale can dip as a project seems insurmountable. Within our team, we remain hyperaware of the difficulty levels of the project or task at hand and the level of experience of the developers involved.

Drive predictable B2B revenue growth with insights from big data and CDPs

As the world reopens and revenue teams are unleashed to meet growth targets, many B2B sellers and marketers are wondering how they can best prioritize prospect accounts. Everyone ultimately wants to achieve predictable revenue growth, but in uncertain times — and with shrinking budgets — it can feel like a pipe dream.

Slimmer budgets likely mean you’ll need more accurate targeting and higher win rates. The good news is your revenue team is likely already gathering tons of prospect data to help you improve account targeting, so it’s time to put that data to work with artificial intelligence. Using big data and four essential AI-based models, you can understand what your prospects want and successfully predict revenue opportunities.

Big data and CDPs are first steps to capturing account insights

Capturing and processing big data is essential in order to know everything about prospects and best position your solution. Accurately targeting your campaigns and buyer journeys necessitates more data than ever before.

Marketers today rely on customer data platforms (CDPs) to handle this slew of information from disparate sources. CDPs let us mash together and clean up data to get a single source of normalized data. We can then use AI to extract meaningful insights and trends to drive revenue planning.

That single source of truth also lets marketers dive into the ocean of accounts and segment them by similar attributes. You can break them down into industry, location, buying stage, intent, engagement — any combination of factors. When it’s time to introduce prospects to your cadence, you’ll have segment-specific insights to guide your campaigns.

AI realizes data-based insights

You might find that your data ocean is much deeper than you expected. While transforming all that data into a single source to drive actionable insights, you’ll also need the right resources and solutions to convert raw data into highly targeted prospect outreach.

This is where AI shines. AI and machine learning enable revenue teams to analyze data for historical and behavioral patterns, pluck out the most relevant intent data, and predict what will move prospects through the buyer journey.

Learning how to ask questions is an essential skill for startup founders

For many of us, learning to ask questions was a matter of the five W’s: who, what, where, when, why (and how).

As I interviewed founders about the most valuable learning resources that allowed them to grow into the leaders they are today, I realized that many of them leaned heavily on carefully crafted approaches to asking questions. In all the interviews, inquiry was by far the most cited learning process. I found these founders to be incredibly methodical, brave, curious, disciplined and efficient in their pursuit of learning.  

Founders showed incredible discipline by approaching information gathering as a structured process. Some founders have a highly systematic approach in how they target their outreach:

I learned by being systematic about talking to people smarter than myself. I needed to know hundreds of people and know what they know. I made a table matrix of who I talk to and for what topic. For example, Eric Schmidt is one of six experts I turn to on establishing management OKRs.

— Reid Hoffman, co-founder of LinkedIn

And in how they catalog/store information about who is an expert …

Learning how to ask questions is an essential skill for startup founders

For many of us, learning to ask questions was a matter of the five W’s: who, what, where, when, why (and how).

As I interviewed founders about the most valuable learning resources that allowed them to grow into the leaders they are today, I realized that many of them leaned heavily on carefully crafted approaches to asking questions. In all the interviews, inquiry was by far the most cited learning process. I found these founders to be incredibly methodical, brave, curious, disciplined and efficient in their pursuit of learning.  

Founders showed incredible discipline by approaching information gathering as a structured process. Some founders have a highly systematic approach in how they target their outreach:

I learned by being systematic about talking to people smarter than myself. I needed to know hundreds of people and know what they know. I made a table matrix of who I talk to and for what topic. For example, Eric Schmidt is one of six experts I turn to on establishing management OKRs.

— Reid Hoffman, co-founder of LinkedIn

And in how they catalog/store information about who is an expert …

Entrepreneurship and investing as social good

2020 has been a year of social upheaval. Around the world, society is identifying different problems in our culture and pushing for widespread change. While there are notable steps we can all take, from altering exclusionary company policies to signing action-oriented petitions, the VC and investment world has another, often overlooked option: Investing in change-the-world startups.

Increasingly, angel investors and institutional funds have begun allocating a portion of their funds to startups focused on diversity and social good, whether focused on democratized access to healthcare and education, or larger scale issues like climate change.

Initially, shifting funds to empower social good may seem like a hefty feat, however investors can embrace this mindshift in three simple steps: (1) redistributing stagnant investments; (2) leveraging democratized access to change-making startups; and (3) identifying founders tracking toward success.

Allocating more investments to foster change

Most of the world’s money is tied up in stagnant places. Whether invested in real estate, bonds or other traditional vehicles, this capital typically often shows conservative returns to investors — and has negligible impact on society. The intent isn’t malicious.

Most family offices and private wealth managers strive to minimize losses and these sorts of uniformed portfolios are safe. Even the most seasoned investors should incorporate more variety into their portfolios, determining where they can make profitable investments that yield higher returns while advancing societal good. Investors can take small steps to get more confident in expanding their strategies.

To start, reframe your thinking into seeing the potential opportunity rather than the risk. A good way to do this: Look at how high-risk public equities performed over the last five years and compare it to ventures within tech. Investors will see a significant disparity and the opportunity to make different returns.

The idea is not to put an entire profile in a single venture. Rather, an investor should take a portion of their portfolio in a high-risk investment sector, like public equities or fund structures, and put it in a similar risk profile with a better return. Gradually increasing these increments, starting at 15% and slowly scaling up, can help investors to see outsized returns while making a difference in the process.

A world of passion at your fingertips

For startups of all sizes, democratized access to investors will accelerate the use of capital for social good. Until recently, only the world’s wealthiest people had exposure to premium capital, but crowdfunding and accelerator programs have ushered in new opportunities, forging connections that might not have otherwise been possible.

These avenues have opened new doors for investors and startups. Access to developed networks or innovation hubs like Silicon Valley are no longer make-or-breaks for those looking to raise capital. Extended global opportunity for startups also means investors have more options to find promising ventures that align with their values, regardless of their location.

But while crowdfunding and accelerators have made the world more accessible, they come with sizable challenges. Despite making early-stage investment more obtainable, crowdfunding often does not bring the most valuable investors to the table.

Crowdfunding also inundates platforms with poor-quality deal flow, making it more strenuous for investors to connect with fruitful opportunities. Meanwhile, various accelerators and incubation platforms have emerged, which have advanced global connection, but tend to be quite noisy.

To succeed, entrepreneurs need more than capital. Rather, they need strategic support from experienced investors who can help them make decisions and scale in an impactful way. With a world of ideas at their fingertips, investors should take time to sift through their options and find the ideas that move them the most, prioritizing quality deals and looking toward platforms that curate promising connections.

Empowering entrepreneurs poised for success

Now is the right time to invest in startups. People who innovate during the pandemic have triple the hustle of those who build in safer economies. But while the timing is right, it’s equally important that the fit is right. I’m a big believer in investing in potential: Ambition, unwavering tenacity and empathy are desirable qualities that can help bring game-changing ideas to fruition.

If an investor funds a passionate leader with a strong vision and ability to attract talent, then the groundwork is laid to build something meaningful. When considering the change-makers to invest in, ask: Is this the right person to be building this company? Do they have the ability to attract and lead talent? Is the market big enough, and is there a significant enough problem to build a company around?

If the answer isn’t yes to all of these questions, it’s important to gauge if you can see a theoretical exit, or if the company is pre-seed or Series A, if they have the ability to scale to a decent size.

Despite this, investing in startups, no matter how good their intentions, can scare investors. One way to overcome trepidation is to invest in larger-stage startups that seem less risky and then wade into earlier-stage startups at your own pace. Special purpose acquisition companies (SPACs) are also becoming an interesting investment option.

SPACs are corporations formed for the sole purpose of raising investment capital through an IPO. The proceeds are then used to buy one or more existing companies, an option that could decrease anxiety for risk-averse investors looking to expand their comfort zone.

Any strategy an investor chooses to embrace social good is a step in the right direction. Capital is a tangible way to fuel innovation and bring about impactful change.

Democratized access to startups yields more opportunity for investors to find ventures that align with their values while diversifying their profiles can provide tremendous results. And when that return means disrupting the status quo and empowering societal change? Everyone wins.

Fundraising lessons from David Rogier of MasterClass

Conventional wisdom says your company should be up and running and have some traction before you raise. But MasterClass co-founder David Rogier says entrepreneurs should try to raise funds before launching.

Before going live, David raised $6.4 million — $1.9 million in a seed round and $4.5 million in a Series A — for what would become MasterClass. To date, the company has raised six funding rounds and secured almost $240 million.

MasterClass’s first investment actually came from Michael Dearing, the founder of VC firm Harrison Metal and one of David’s business school professors. After graduating from Stanford University Graduate School of Business, David started working for Michael at the firm. About a year in, he quit to start his own company.

When David gave his notice, Michael told him he would invest just under $500,000, even though David didn’t have an idea yet.

“I was honored, I was thrilled and I was terrified, all within the span of 10 seconds,” David says. “It was an amazing gift, but I also felt an immense amount of pressure. I knew this was a once-in-a-lifetime chance, and I didn’t want to mess it up.”

He drew a blank for a year, but finally got inspiration from a story his grandmother told him when he was in second grade. In it, she stressed the importance of education, the one thing no one can ever take away from you. Upon remembering that lesson, David knew he wanted to give as many people as possible the opportunity to learn from the best, and MasterClass was born.

In an episode of How I Raised It, David shares some of his secrets to raising capital.

First money, then metrics

Securing funding before you even launch your company definitely isn’t a common practice. But David is adamant that you should attempt it.

“Your metrics out of the gate are never going to be great,” David says. “You need enough funds to have the time to actually improve them.” At the beginning, instead of relying on data, you should sell investors on your vision.

Of course, this is easier said than done. Many investors don’t want to give you a dime until you’ve proven your concept works. To overcome this barrier, David figured out what he could do to help minimize risk for investors.

Tech must radically rethink how it treats independent contractors

Despite a surging stock market and many major tech players having record quarters, we’re still seeing layoffs throughout tech and the rest of corporate America. Salesforce recorded a huge quarter, passing $5 billion in revenue, only to lay off around 1000 people. LinkedIn is laying off 960 people one day after reporting a 10% increase in revenue.

These layoffs may seem like a contraction in size for these huge enterprises, but it’s actually the beginning of something I call The Great Unbundling of Corporate America. They still need to grow, they still need to innovate, they still need to get work done and they’re not simply canceling projects and giving up on contracts.

Just as COVID-19 has accelerated the move to remote work, our current crisis has accelerated the trend toward hiring independent contractors. Back in 2019 a New York Times report found that Google had a shadow workforce of 121,000 temporary workers and contractors, overshadowing their 102,000 full-timers. ZipRecruiter reported in 2018 that tech, along with its record employment growth, was showing an increasing share of listings for independent contractors.

A study from the Bureau of Labor Statistics found that between 6.9% and 9.6% of all workers are now independent contractors, and according to Upwork, that may be as high as 35%. Mark my words — companies are using this time as an opportunity to swing the pendulum toward independent contractors and trimming the fat, justifying it with a vague gesture toward “an unprecedented time.”

That’s why, in my opinion, you’re seeing the NASDAQ hitting record highs despite everyone’s turmoil — depressingly, investors can see that large companies are tightening up and cleaning up waste, while finding an affordable workforce at will. As they have unbundled themselves from our physical offices, large enterprises are going to unbundle themselves from having to have a set number of employees.

When Square allowed its entire workforce to work remotely permanently. It wasn’t just because they wanted them to feel more creative and productive, but was likely a move away from having quite as much expensive, needless office space.

Similarly, if there is work that a full-time employee does that could be done by a flexible, independent contractor, why not make that change too? And it’ll be a lot easier to make without as many people at the office.

The argument I’m making is not anti-contractor, though.

I can’t think of any point in history where it’s been better to create a freelance business — the startup costs are significantly lower, and as companies move toward remote work, you can theoretically take business nationally (or internationally) like never before. Companies’ moves toward replacing W-2 workers with contractors is an opportunity for people to create their own miniature freelance empires, unbundling themselves from corporate America’s required hours, and potentially creating a way to weather future storms by taking away any single company’s leverage on their income.

The rush to remote work is also likely to push more workers into the freelance economy too. By having to create a remote office, with a remote presence in meetings and having to manage and organize our days, the average worker has all but adjusted to the life of a freelancer.

Where some might have gone to an office and had things simply happen to them, the remote world requires an attention to your calendar and active outreach to colleagues that, well, models how one might run a freelance business. Those with core skillsets that can be marketed and sold to multiple clients should be thinking about whether being a wage slave is necessary anymore, and with good reason.

That said — corporate America, and especially tech, has to treat this essential workforce with a great deal more empathy and respect than they have thus far.

Uber and Lyft were ordered to treat drivers as employees in part due to the fact that they never treated their contractors like parts of the company. Other than the obvious lack of benefits (paid time off, health insurance, etc.), Uber, like many large enterprises, treats contractors as disposable rather than flexible, despite them being the literal driving force of the company. When Uber went public, they gave a nominal bonus for drivers that had completed 2500 to 40,000 trips, with a chance to buy up to $10,000 of stock — at the IPO price. These drivers, that had been the very reason that many people became millionaires and billionaires when Uber went public, were given the chance to maybe make money, if they sold the stock quickly enough.

It’s an abject lesson on how to not build loyalty with independent contractors. It’s also a lesson on what the next big company that wants to build themselves off the back of the 1099’er should do.

What I’m suggesting is a radical rethinking of freelance contracting. I want you to see independent contractors as a different kind of worker, not as a way of skirting getting a full-time employee. A freelancer, by definition, is someone that you don’t monopolize, and someone that you should actively give agency and, indeed, part of the network you’re building. One of the issues of corporate America’s approach to freelance work is an us-versus-them approach to employment — you’re either part of us or you’re simply a thing we pick up and put down. What I’m suggesting is treating your freelancers as an essential part of your strategy, and compensating them as such. Freelancers should own equity and should have skin in the game — they may be working with you on a number of projects and take literal ownership of vast successes throughout your history.

Contracted work has only become mercenary through the treatment of the freelance worker. Where tech has succeeded in creating hundreds of thousands of independent contractor positions, it also has to lead the way in reimagining how we may treat them and reward them for their work. And corporate America needs to take a step beyond simply seeing them as a cheaper, easier way to do business. They’re so much more.

Are high churn rates depressing earnings for app developers?

Ever since Apple opened up subscription monetization to more apps in 2016 — and enticed developers with an 85/15 split on revenue from customers that remain subscribed for more than a year — subscription monetization and retention has felt like the Holy Grail for app developers. So much so that Google quickly followed suit in what appeared to be an example of healthy competition for developers in the mobile OS duopoly.

But how does that split actually work out for most apps? Turns out, the 85/15 split — which Apple is keen to mention anytime developers complain about the App Store rev share — doesn’t have a meaningful impact for most developers. Because churn.

No matter how great an app is, subscribers are going to churn. Sometimes it’s because of a credit card expiring or some other billing issue. And sometimes it’s more of a pause, and the user comes back after a few months. But the majority of churn comes from subscribers who, for whatever reason, decide that the app just isn’t worth paying for anymore. If a subscriber churns before the one-year mark, the developer never sees that 85% split. And even if the user resubscribes, Apple and Google reset the clock if a subscription has lapsed for more than 60 days. Rather convenient… for Apple and Google.

Top mobile apps like Netflix and Spotify report churn rates in the low single digits, but they are the outliers. According to our data, the median churn rate for subscription apps is around 13% for monthly subscriptions and around 50% for annual. Monthly subscription churn is generally a bit higher in the first few months, then it tapers off. But an average churn of 13% leaves just 20% of subscribers crossing that magical 85/15 threshold.

In practice, what this means is that, for all the hype around the 85/15 split, very few developers are going to see a meaningful increase in revenue: