Including a range of plastics, ceramics and metals like titanium with varying results
Earlier this month, tech moguls Elon Musk and Mark Zuckerberg debated the pros and cons of artificial intelligence from different corners of the internet. While SpaceX’s CEO is more of an alarmist, insisting that we should approach AI with caution and that it poses a “fundamental existential risk,” Facebook’s founder leans toward a more optimistic future, dismissing “doomsday scenarios” in favor of AI helping us build a brighter future.
I now agree with Zuckerberg’s sunnier outlook—but I didn’t used to.
Beginning my career as an engineer, I was interested in AI, but I was torn about whether advancements would go too far too fast. As a mother with three kids entering their teens, I was also worried that AI would disrupt the future of my children’s education, work, and daily life. But then something happened that forced me into the affirmative.
Imagine for a moment that you are a pathologist and your job is to scroll through 1,000 photos every 30 minutes, looking for one tiny outlier on a single photo. You’re racing the clock to find a microscopic needle in a massive data haystack.
Now, imagine that a woman’s life depends on it. Mine.
This is the nearly impossible task that pathologists are tasked with every day. Treating the 250,000 women in the US who will be diagnosed with breast cancer this year, each medical worker must analyze an immense amount of cell tissue to identify if their patient’s cancer has spread. Limited by time and resources, they often get it wrong; a recent study found that pathologists accurately detect tumors only 73.2% of the time.
In 2011 I found a lump in my breast. Both my family doctor and I were confident that it was a Fibroadenoma, a common noncancerous (benign) breast lump, but she recommended I get a mammogram to make sure. While the original lump was indeed a Fibroenoma, the mammogram uncovered two unknown “spots.” My journey into the unknown started here.
Since AI imaging was not available at the time, I had to rely solely on human analysis. The next four years were a blur of ultrasounds, biopsies, and surgeries. My well-intentioned network of doctors and specialists were not able to diagnose or treat what turned out to be a rare form of cancer, and repeatedly attempted to remove my recurring tumors through surgery.
After four more tumors, five more biopsies, and two more operations, I was heading toward a double mastectomy and terrified at the prospect of the cancer spreading to my lungs or brain.
I knew something needed to change. In 2015, I was introduced to a medical physicist that decided to take a different approach, using big data and a machine-learning algorithm to spot my tumors and treat my cancer with radiation therapy. While I was nervous about leaving my therapy up to this new technology, it—combined with the right medical knowledge—was able to stop the growth of my tumors. I’m now two years cancer-free.
I was thankful for the AI that saved my life— but then that very same algorithm changed my son’s potential career path.
The positive impact of machine learning is often overshadowed by the doom-and-gloom of automation. Fearing for their own jobs and their children’s future, people often choose to focus on the potential negative repercussions of AI rather than the positive changes it can bring to society.
After seeing what this radiation treatment was able to do for me, my son applied to a university program in radiology technology to explore a career path in medical radiation. He met countless radiology technicians throughout my years of treatment and was excited to start his training off in a specialized program. However, during his application process, the program was cancelled: He was told it was because there were no longer enough jobs in the radiology industry to warrant the program’s continuation. Many positions have been lost to automation—just like the technology and machine learning that helped me in my battle with cancer.
This was a difficult period for both my son and I: The very thing that had saved my life prevented him from following the path he planned. He had to rethink his education mid-application when it was too late to apply for anything else, and he was worried that his back up plans would fall through.
He’s now pursuing a future in biophysics rather than medical radiation, starting with an undergraduate degree in integrated sciences. In retrospect, we both now realize that the experience forced him to rethink his career and unexpectedly opened up his thinking about what research areas will be providing the most impact on people’s lives in the future.
Although some medical professionals will lose their jobs to AI, the life-saving benefits to patients will be magnificent. Beyond cancer detection and treatment, medical professionals are using machine learning to improve their practice in many ways. For instance, Atomwise applies AI to fuel drug discovery, Deep Genomics uses machine learning to help pharmaceutical companies develop genetic medicines, and Analytics 4 Life leverages AI to better detect coronary artery disease.
While not all transitions from automated roles will be as easy as my son’s pivot to a different scientific field, I believe that AI has the potential to shape our future careers in a positive way, even helping us find jobs that make us happier and more productive.
As this technology rapidly develops, the future is clear: AI will be an integral part of our lives and bring massive changes to our society. It’s time to stop debating (looking at you, Musk and Zuckerberg) and start accepting AI for what it is: both the good and the bad.
Throughout the years, I’ve found myself on both sides of the equation, arguing both for and against the advancement of AI. But it’s time to stop taking a selective view on AI, choosing to incorporate it into our lives only when convenient. We must create solutions that mitigate AI’s negative impact and maximize its positive potential. Key stakeholders—governments, corporates, technologists, and more—need to create policies, join forces, and dedicate themselves to this effort.
And we’re seeing great progress. AT&T recently began retraining thousands of employees to keep up with technology advances and Google recently dedicated millions of dollars to prepare people for an AI-dominated workforce. I’m hopeful that these initiatives will allow us to focus on all the good that AI can do for our world and open our eyes to the potential lives it can save.Discover More