"Better and personalized healthcare through AI is still a hugely challenging problem that will take an army of scientists and engineers." Photo via UH.edu

We are currently in the midst of what some have called the "wild west" of AI. Though healthcare is one of the most heavily regulated sectors, the regulation of AI in this space is still in its infancy. The rules are being written as we speak. We are playing catch-up by learning how to reap the benefits these technologies offer while minimizing any potential harms once they've already been deployed.

AI systems in healthcare exacerbate existing inequities. We've seen this play out into real-world consequences from racial bias in the American justice system and credit scoring, to gender bias in resume screening applications. Programs that are designed to bring machine "objectivity" and ease to our systems end up reproducing and upholding biases with no means of accountability.

The algorithm itself is seldom the problem. It is often the data used to program the technology that merits concern. But this is about far more than ethics and fairness. Building AI tools that take account of the whole picture of healthcare is fundamental to creating solutions that work.

The Algorithm is Only as Good as the Data

By nature of our own human systems, datasets are almost always partial and rarely ever fair. As Linda Nordling comments in a Nature article, A fairer way forward for AI in healthcare, "this revolution hinges on the data that are available for these tools to learn from, and those data mirror the unequal health system we see today."

Take, for example, the finding that Black people in US emergency rooms are 40 percent less likely to receive pain medication than are white people, and Hispanic patients are 25 percent less likely. Now, imagine the dataset these findings are based on is used to train an algorithm for an AI tool that would be used to help nurses determine if they should administer pain relief medication. These racial disparities would be reproduced and the implicit biases that uphold them would remain unquestioned, and worse, become automated.

We can attempt to improve these biases by removing the data we believe causes the bias in training, but there will still be hidden patterns that correlate with demographic data. An algorithm cannot take in the nuances of the full picture, it can only learn from patterns in the data it is presented with.

Bias Creep

Data bias creeps into healthcare in unexpected ways. Consider the fact that animal models used in laboratories across the world to discover and test new pain medications are almost entirely male. As a result, many medications, including pain medication, are not optimized for females. So, it makes sense that even common pain medications like ibuprofen and naproxen have been proven to be more effective in men than women and that women tend to experience worse side effects from pain medication than men do.

In reality, male rodents aren't perfect test subjects either. Studies have also shown that both female and male rodents' responses to pain levels differ depending on the sex of the human researcher present. The stress response elicited in rodents to the olfactory presence of a sole male researcher is enough to alter their responses to pain.

While this example may seem to be a departure from AI, it is in fact deeply connected — the current treatment choices we have access to were implicitly biased before the treatments ever made it to clinical trials. The challenge of AI equity is not a purely technical problem, but a very human one that begins with the choices that we make as scientists.

Unequal Data Leads to Unequal Benefits

In order for all of society to enjoy the many benefits that AI systems can bring to healthcare, all of society must be equally represented in the data used to train these systems. While this may sound straightforward, it's a tall order to fill.

Data from some populations don't always make it into training datasets. This can happen for a number of reasons. Some data may not be as accessible or it may not even be collected at all due to existing systemic challenges, such as a lack of access to digital technology or simply being deemed unimportant. Predictive models are created by categorizing data in a meaningful way. But because there's generally less of it, "minority" data tends to be an outlier in datasets and is often wiped out as spurious in order to create a cleaner model.

Data source matters because this detail unquestionably affects the outcome and interpretation of healthcare models. In sub-Saharan Africa, young women are diagnosed with breast cancer at a significantly higher rate. This reveals the need for AI tools and healthcare models tailored to this demographic group, as opposed to AI tools used to detect breast cancer that are only trained on mammograms from the Global North. Likewise, a growing body of work suggests that algorithms used to detect skin cancer tend to be less accurate for Black patients because they are trained mostly on images of light-skinned patients. The list goes on.

We are creating tools and systems that have the potential to revolutionize the healthcare sector, but the benefits of these developments will only reach those represented in the data.

So, what can be done?

Part of the challenge in getting bias out of data is that high volume, diverse and representative datasets are not easy to access. Training datasets that are publicly available tend to be extremely narrow, low-volume, and homogenous—they only capture a partial picture of society. At the same time, a wealth of diverse health data is captured every day in many healthcare settings, but data privacy laws make accessing these more voluminous and diverse datasets difficult.

Data protection is of course vital. Big Tech and governments do not have the best track record when it comes to the responsible use of data. However, if transparency, education, and consent for the sharing of medical data was more purposefully regulated, far more diverse and high-volume data sets could contribute to fairer representation across AI systems and result in better, more accurate results for AI-driven healthcare tools.

But data sharing and access is not a complete fix to healthcare's AI problem. Better and personalized healthcare through AI is still a hugely challenging problem that will take an army of scientists and engineers. At the end of the day, we want to teach our algorithms to make good choices but we are still figuring out what good choices should look like for ourselves.

AI presents the opportunity to bring greater personalization to healthcare, but it equally presents the risk of entrenching existing inequalities. We have the opportunity in front of us to take a considered approach to data collection, regulation, and use that will provide a fuller and fairer picture and enable the next steps for AI in healthcare.

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Angela Wilkins is the executive director of the Ken Kennedy Institute at Rice University.

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CultureMap Emails are Awesome

7 lessons from a Houston-based unicorn startup founder

taking notes

At a fireside chat at SXSW, a Houston founder pulled back the curtain on his entrepreneurial journey that's taken him from an idea of how to make the chemicals industry more sustainable to a company valued at over $2 billion.

Gaurab Chakrabarti, the CEO and co-founder of Solugen, joined the Greater Houston Partnership's Houston House at SXSW on Monday, March 13, for a discussion entitled, "Building a Tech Unicorn." In the conversation with Payal Patel, principal of Softeq Ventures, he share the trials and tribulations from the early days of founding Solugen. The company, which has raised over $600 million since its founding in 2016, has an innovative and carbon negative process of creating plant-derived substitutes for petroleum-based products.

The event, which quickly reached capacity with eager SXSW attendees, allowed Chakrabarti to instill advice on several topics — from early customer acquisition and navigating VC investing to finding the right city to grow in and setting up a strong company culture.

Here are seven pieces of startup advice from Chakrabarti's talk.

1. Don’t be near a black hole.

Chakrabarti began his discussion addressing the good luck he's had standing up Solugen. He's the first to admit that luck is an important element to his success, but he says, as a founder, you can set yourself up for luck in a handful of ways.

“You do make your own luck, but you have to be putting in the work to do it," Chakrabarti says, adding that it's not an easy thing to accomplish. “There are things you can be doing to increase your luck surface area."

One of the principals he notes on is not surrounding yourself with black holes. These are people who don't believe in your idea, or your ability to succeed, Chakrabarti explains, referencing a former dean who said he was wasting his talent on his idea for Solugen.

2. The co-founder dynamic is the most important thing.

Early on, Chakrabarti emphasizes how important having a strong co-founder relationship is, crediting Solugen's co-founder and CTO Sean Hunt for being his "intellectual ping-pong partner."

“If you have a co-founder, that is the thing that’s going to make or break your company,” he says. “It’s not your idea, and it’s not your execution — it’s your relationship with your co-founder.”

Hunt and Chakrabarti have been friends for 12 years, Chakrabarti says, and, that foundation and the fact that they've been passionate about their product since day one, has been integral for Solugen's success.

"We had a conviction that we were building something that could be impactful to the rest of the world," he says.

3. Confirm a market of customers early on.

Chakrabarti says that in the early days of starting his company, he didn't have a concept of startup accelerators or other ways to access funding — he just knew he had to get customers to create revenue as soon as possible.

He learned about the growing float spa industry, and how a huge cost for these businesses was peroxide that was used to sanitize the water in the floating pods. Chakrabarti and Hunt had created a small amount of what they were calling bioperoxide that they could sell at a cheaper cost to these spas and still pocket a profit.

“We ended up owning 80 percent of the float spa market,” Chakrabarti says. “That taught us that, ‘wow, there’s something here.”

While it was unglamourous work to call down Texas float spas, his efforts secured Solugen's first 100 or so customers and identified a path to profitability early on.

“Find your niche market that allows you to justify that your technology or product that has a customer basis,” Chakrabarti says on the lesson he learned through this process.

4. Find city-company fit.

While Chakrabarti has lived in Houston most of his life, the reason Solugen is headquartered in Houston is not due to loyalty of his hometown.

In fact, Chakrabarti shared a story of how a potential seed investor asked Chakrabarti and Hunt to move their company to the Bay Area, and the co-founders refused the offer and the investment.

“There’s no way our business could succeed in the Bay Area," Chakrabarti says. He and Hunt firmly believed this at the time — and still do.

“For our business, if you look at the density of chemical engineers, the density of our potential customers, and the density of people who know how to do enzyme engineering, Houston happened to be that perfect trifecta for us," he explains.

He argues that every company — software, hardware, etc. — has an opportunity to find their ideal city-company fit, something that's important to its success.

5. Prove your ability to execute.

When asked about pivots, Chakrabarti told a little-known story of how Solugen started a commercial cleaning brand. The product line was called Ode to Clean, and it was marketed as eco-friendly peroxide wipes. At the time, Solugen was just three employees, and the scrappy team was fulfilling orders and figuring out consumer marketing for the first time.

He says his network was laughing at the idea of Chakrabarti creating this direct-to-consumer cleaning product, and it was funny to him too, but the sales told another story.

At launch, they sold out $1 million of inventory in one week. But that wasn't it.

“Within three months, we got three acquisition offers," Chakrabarti says.

The move led to a brand acquisition of the product line, with the acquirer being the nation's largest cleaning wipe provider. It meant three years of predictable revenue that de-risked the business for new investors — which were now knocking on Solugen's door with their own investment term sheets.

“It told the market more about us as a company,” he says. “It taught the market that Solugen is a company that is going to survive no matter what. … And we’re a team that can execute.”

What started as a silly idea led to Solugen being one step closer to accomplishing its long-term goals.

“That pivot was one of the most important pivots in the company’s history that accelerated our company’s trajectory by four or five years," Chakrabarti says.

6. Adopt and maintain a miso-management style.

There's one lesson Chakrabarti says he learned the hard way, and that was how to manage his company's growing team. He shares that he "let go of the reins a bit" at the company's $400-$500 million point. He says that, while there's this idea that successful business leaders can hire the best talent that allows them to step back from the day-to-day responsibilities, that was not the right move for him.

“Only founders really understand the pain points of the business," Chakrabarti says. "Because it’s emotionally tied to you, you actually feel it."

Rather than a micro or macro-management style, Chakrabarti's describes his leadership as meso-management — something in between.

The only difference, Chakrabarti says, is how he manages his board. For that group, he micromanages to ensure that they are doing what's best for his vision for Solugen.

7. Your culture should be polarizing.

Chakrabarti wrapped up his story on talking about hiring and setting up a company culture for Solugen. The company's atmosphere is not for everyone, he explains.

“If you’re not polarizing some people, it’s not a culture,” Chakrabarti says, encouraging founders to create a culture that's not one size fits all.

He says he was attracted to early employees who got mad at the same things he did — that passion is what makes his team different from others.

Houston tech company to acquire IT infrastructure startup

M&A moves

Hewlett Packard Enterprise has announced its plans to acquire a San Jose, California-based startup.

HPE, which relocated its headquarters to Houston from the Bay Area a couple years ago, has agreed to acquire OpsRamp, a software-as-a-service company with an IT operations management, or ITOM, platform that can monitor, automate, and manage IT infrastructure, cloud resources, and more.

According to a news release from HPE, the OpsRamp platform will be merged with the HPE GreenLake edge-to-cloud platform, which supports more than 65,000 customers, powers over two million connected devices, and manages more than one exabyte of data with customers worldwide.

The new integrated system "will reduce the operational complexity of multi-vendor and multi-cloud IT environments that are in the public cloud, colocations, and on-premises," per the statement.

“Customers today are managing several different cloud environments, with different IT operational models and tools, which dramatically increases the cost and complexity of digital operations management,” says HPE's CTO Fidelma Russo in the release. “The combination of OpsRamp and HPE will remove these barriers by providing customers with an integrated edge-to-cloud platform that can more effectively manage and transform multi-vendor and multi-cloud IT estates.

"This acquisition advances HPE hybrid cloud leadership and expands the reach of the HPE GreenLake platform into IT Operations Management,” she continues.

HPE's corporate venture arm, Pathfinder, invested in OpsRamp in 2020. The company raised $57.5 million prior to the acquisition. Other investors included Morgan Stanley Expansion Capital and Sapphire Ventures, per TechCrunch.

“The integration of OpsRamp’s hybrid digital operations management solution with the HPE GreenLake platform will provide an unmatched offering for organizations seeking to innovate and thrive in a complex, multi-cloud world. Partners and the channel will also play a pivotal role to advance their as-a-service offerings, as enterprises look for a unified approach to better manage their operations from the edge to the cloud,” says Varma Kunaparaju, CEO of OpsRamp, in the release.

“We look forward to leveraging the scale and reach of HPE’s global go-to-market engine to deliver our unique offering and are excited for this journey ahead as part of HPE.”

3 Houston innovators to know this week

Editor's note: In this week's roundup of Houston innovators to know, I'm introducing you to three local innovators across industries — from space tech to software development — recently making headlines in Houston innovation.


Michael Suffredini, CEO and president of Axiom Space

Axiom's CEO announced a new mission and space suit design. Photo courtesy of Axiom Space

It was a big news week for Axiom Space. The Houston company announced its next commercial space mission with NASA to the International Space Station a day before it unveiled its newly design space suit that will be donned by the astronauts headed to the moon.

“We’re carrying on NASA’s legacy by designing an advanced spacesuit that will allow astronauts to operate safely and effectively on the Moon,” says Micahel Suffredini, CEO of Axiom, in a statement. “Axiom Space’s Artemis III spacesuit will be ready to meet the complex challenges of the lunar south pole and help grow our understanding of the Moon in order to enable a long-term presence there.”

Called the Axiom Extravehicular Mobility Unit, or AxEMU, the prototype was revealed at Space Center Houston’s Moon 2 Mars Festival on March 15. According to Axiom, a full fleet of training spacesuits will be delivered to NASA by late this summer. Read more.

Julie King, president of NB Realty Partners

Houston's access to lab space continues to be a challenge for biotech companies. Photo via Getty Images

In terms of Houston developing as an attractive hub for biotech companies, Julie King says the city still has one major obstacle: Available lab space.

She writes in a guest column for InnovationMap that biotech startups need specialized space that can hold the right equipment. That's not cheap, and it's usually a challenge for newer companies to incur that cost.

"However, with realistic expectations about these challenges, the good news is that once settled into a facility that is a fit, Houston’s emerging biotech companies can thrive and grow," she writes. Read more.

Owen Goode, executive vice president at Zaelot

Houston software development firm Axon is planning its Texas expansion thanks to its recent acquisition. Photo via LinkedIn

Owen Goode is a huge fan of Houston. That's why when his software design firm, Axon, got acquired by Zaelot, led by CEO Jeff Lombard, in January, he made sure the deal would mean growth in the region.

Zaelot is a global, software firm with a presence in 14 countries, mostly focused in the United States, Uruguay, and Iceland. With the acquisition of Axon, the combined company is poised to expand in Texas, beginning in Houston, Goode says.

“Together we have a strong suite of offerings across a wide variety of domains including full-stack development, cloud/data engineering, design, staff augmentation, project management, and software architecture. We also have experience in multiple domains, including health care, aviation, defense, finance, and startups,” says Goode. Read more.