In a guest column, these lawyers explain the pros and cons of using AI for hiring. Photo via Getty Images

Workplace automation has entered the human resource department. Companies rely increasingly on artificial intelligence to source, interview, and hire job applicants. These AI tools are marketed to save time, improve the quality of a workforce, and eliminate unlawful hiring biases. But is AI incapable of hiring discrimination? Can a company escape liability for discriminatory hiring because, "the computer did it?"

Ultimately, whether AI is a solution or a landmine depends on how carefully companies implement the technology. AI is not immune from discrimination and federal law holds companies accountable for their hiring decisions, even if those decisions were made in a black server cabinet. The technology can mitigate bias, but only if used properly and monitored closely.

Available AI tools

The landscape of AI technology is continually growing and covers all portions of the hiring process — recruiting, interviewing, selection, and onboarding. Some companies use automated candidate sourcing technology to search social media profiles to determine which job postings should be advertised to particular candidates. Others use complex algorithms to determine which candidates' resumes best match the requirements of open positions. And some employers use video interview software to analyze facial expressions, body language, and tone to assess whether a candidate exhibits preferred traits.

Federal anti-discrimination law

Although AI tools likely have no intent to unlawfully discriminate, that does not absolve them from liability. This is because the law contemplates both intentional discrimination (disparate treatment) as well as unintentional discrimination (disparate impact). The larger risk for AI lies with disparate impact claims. In such lawsuits, intent is irrelevant. The question is whether a facially neutral policy or practice (e.g., use of an AI tool) has a disparate impact on a particular protected group, such as on one's race, color, national origin, gender, or religion.

The Equal Employment Opportunity Commission, the federal agency in charge of enforcing workplace anti-discrimination laws, has demonstrated an interest in AI and has indicated that such technology is not an excuse for discriminatory impacts.

Discrimination associated with AI tools

The diversity of AI tools means that each type of technology presents unique potential for discrimination. One common thread, however, is the potential for input data to create a discriminatory impact. Many algorithms rely on a set of inputs to understand search parameters. For example, a resume screening tool is often set up by uploading sample resumes of high-performing employees. If those resumes favor a particular race or gender, and the tool is instructed to find comparable resumes, then the technology will likely reinforce the existing homogeneity.

Some examples are less obvious. Sample resumes may include employees from certain zip codes that are home to predominately one race or color. An AI tool may favor those zip codes, disfavoring applicants from other zip codes of different racial composition. Older candidates may be disfavored by an algorithm's preference for ".edu" email addresses. In short, if a workforce is largely comprised of one race or one gender, having the tool rely on past hiring decisions could negatively impact applicants of another race or gender.

Steps to mitigate risk

There are a handful of steps that employers can take to use these technologies and remain compliant with anti-discrimination laws.

First, companies should demand that AI vendors disclose as much as possible about how their products work. Vendors may be reticent to disclose details about proprietary information, but employers will ultimately be responsible for discriminatory impacts. Thus, as part of contract negotiations, a company should consider seeking indemnification from the vendor for discrimination claims.

Second, companies should consider auditing the tool to ensure it does not yield a disparate impact on protected individuals. Along the same lines, companies should be careful in selecting input data. If the inputs reflect a diverse workforce, a properly functioning algorithm should, in theory, replicate that diversity.

Third, employers should stay abreast of developments in the law. This is an emerging field and state legislators have taken notice. Illinois recently passed regulation governing the use of AI in the workplace and other states, including New York, have introduced similar bills.

AI can solve many hiring challenges and help cultivate a more diverse and qualified workforce. But the tools are often only as unbiased as the creators and users of that technology. Careful implementation will ensure AI becomes a discrimination solution — not a landmine.

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Kevin White is a partner and Dan Butler is an associate with Hunton Andrews Kurth LLP, which has an office in Houston.

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Texas nonprofit grants $68.5M to Houston organizations for recruitment, research

Three prominent institutions in Houston will be able to snag a trio of high-profile cancer researchers thanks to $12 million in new funding from the Cancer Prevention and Research Institute of Texas.

The biggest recruitment award — $6 million — went to the University of Texas MD Anderson Center to lure researcher Xiling Shen away from the Terasaki Institute for Biomedical Innovation in Los Angeles.

Shen is chief scientific officer at the nonprofit Terasaki Institute. His lab there studies precision medicine, including treatments for cancer, from a “systems biology perspective.”

He also is co-founder and former CEO of Xilis, a Durham, North Carolina-based oncology therapy startup that raised $70 million in series A funding in 2021. Before joining the institute in 2021, the Stanford University graduate was an associate professor at Duke University in Durham.

Shen and Xilis aren’t strangers to MD Anderson.

In 2023, MD Anderson said it planned to use Xilis’ propriety MicroOrganoSphere (MOS) technology for development of novel cancer therapies.

“Our research suggests the MOS platform has the potential to offer new capabilities and to improve the efficiency of developing innovative drugs and cell therapies over current … models, which we hope will bring medicines to patients more quickly,” Shen said in an MD Anderson news release.

Here are the two other Cancer Prevention and Research Institute of Texas (CPRIT) awards that will bring noted cancer researchers to Houston:

  • $4 million to attract David Sarlah to Rice University from the University of Illinois, where he is an associate professor of chemistry. Sarlah’s work includes applying the principles of chemistry to creation of new cancer therapies.
  • $2 million to lure Vishnu Dileep to the Baylor College of Medicine from the Massachusetts Institute of Technology (MIT), where he is a postdoctoral fellow. His work includes the study of cancer genomes.

CPRIT also handed out more than $56.5 million in grants and awards to seven institutions in the Houston area. Here’s the rundown:

  • MD Anderson Cancer Center — Nearly $25.6 million
  • Baylor College of Medicine — Nearly $11.5 million
  • University of Texas Health Science Center at Houston — More than $6 million
  • Rice University — $4 million
  • University of Texas Medical Branch at Galveston — More than $3.5 million
  • Methodist Hospital Research Institute — More than $3.3 million
  • University of Houston — $1.4 million

Dr. Pavan Reddy, a CPRIT scholar who is a professor at the Baylor College of Medicine and director of its Dan L Duncan Comprehensive Cancer Care Center, says the CPRIT funding “will help our investigators take chances and explore bold ideas to make innovative discoveries.”

The Houston-area funding was part of nearly $99 million in grants and awards that CPRIT recently approved.

Houston space company's lunar lander touches down on the moon in historic mission

touchdown

A private lander on Thursday made the first U.S. touchdown on the moon in more than 50 years, but managed just a weak signal back until flight controllers scrambled to gain better contact.

Despite the spotty communication, Intuitive Machines, the company that built and managed the craft, confirmed that it had landed upright. But it did not provide additional details, including whether the lander had reached its intended destination near the moon’s south pole. The company ended its live webcast soon after identifying a lone, weak signal from the lander.

“What we can confirm, without a doubt, is our equipment is on the surface of the moon,” mission director Tim Crain reported as tension built in the company’s Houston control center.

Added Intuitive Machines CEO Steve Altemus: “I know this was a nail-biter, but we are on the surface and we are transmitting. Welcome to the moon.”

Data was finally starting to stream in, according to a company announcement two hours after touchdown.

The landing put the U.S. back on the surface for the first time since NASA’s famed Apollo moonwalkers.

Intuitive Machines also became the first private business to pull off a lunar landing, a feat achieved by only five countries. Another U.S. company, Astrobotic Technology, gave it a shot last month, but never made it to the moon, and the lander crashed back to Earth. Both companies are part of a NASA-supported program to kick-start the lunar economy.

Astrobotic was among the first to relay congratulations. “An incredible achievement. We can’t wait to join you on the lunar surface in the near future,” the company said via X, formerly Twitter.

Intuitive Machines “aced the landing of a lifetime,” NASA Administrator Bill Nelson tweeted.

The final few hours before touchdown were loaded with extra stress when the lander's laser navigation system failed. The company's flight control team had to press an experimental NASA laser system into action, with the lander taking an extra lap around the moon to allow time for the last-minute switch.

With this change finally in place, Odysseus descended from a moon-skimming orbit and guided itself toward the surface, aiming for a relatively flat spot among all the cliffs and craters near the south pole.

As the designated touchdown time came and went, controllers at the company's command center anxiously awaited a signal from the spacecraft some 250,000 miles (400,000 kilometers) away. After close to 15 minutes, the company announced it had received a weak signal from the lander.

Launched last week, the six-footed carbon fiber and titanium lander — towering 14 feet (4.3 meters) — carried six experiments for NASA. The space agency gave the company $118 million to build and fly the lander, part of its effort to commercialize lunar deliveries ahead of the planned return of astronauts in a few years.

Intuitive Machines' entry is the latest in a series of landing attempts by countries and private outfits looking to explore the moon and, if possible, capitalize on it. Japan scored a lunar landing last month, joining earlier triumphs by Russia, U.S., China and India.

The U.S. bowed out of the lunar landscape in 1972 after NASA's Apollo program put 12 astronauts on the surface. Astrobotic of Pittsburgh gave it a shot last month, but was derailed by a fuel leak that resulted in the lander plunging back through Earth's atmosphere and burning up.

Intuitive Machines’ target was 186 miles (300 kilometers) shy of the south pole, around 80 degrees latitude and closer to the pole than any other spacecraft has come. The site is relatively flat, but surrounded by boulders, hills, cliffs and craters that could hold frozen water, a big part of the allure. The lander was programmed to pick, in real time, the safest spot near the so-called Malapert A crater.

The solar-powered lander was intended to operate for a week, until the long lunar night.

Besides NASA’s tech and navigation experiments, Intuitive Machines sold space on the lander to Columbia Sportswear to fly its newest insulating jacket fabric; sculptor Jeff Koons for 125 mini moon figurines; and Embry-Riddle Aeronautical University for a set of cameras to capture pictures of the descending lander.