Can You Spot the AI?
One of the articles in this issue was written by an AI content generator. We edited the verbiage slightly to ensure it matched the ProAssurance style guide but left the information in the text accurate to what the algorithm generated.
Can you spot which article came from the ProAssurance editorial team, and which one is from a robot? We’ll reveal the results later in this issue.
- Claims: Laura Ekery
- Underwriting: John Alexander
- Risk Management: Jennifer Freeden
Claims: Laura Ekery
The Claims department is optimistic about the potential to use AI in all aspects of our business, from evaluating and identifying risks, to promoting management of risks, analyzing appropriate reserves, and forecasting claim outcomes. ProAssurance is actively investigating how and where AI can be used to improve service by enhancing our insureds’ digital experience and encouraging retention and enhanced services to each insured. Claims’ efforts will focus on enhanced efficiency and effective evaluation of all aspects of claims. These aspects currently include analysis of attorney fees and outcomes and efficient review of medical records.
AI and its endless possibilities offer great promise for the future. We intend to harness its potential to become better, faster, and more effective.
Underwriting: John Alexander
It seems like AI could speed up many basic underwriting processes. I am learning and absorbing all that I can about AI so that I understand the specific impacts it will bring to our business. I anticipate AI will produce time savings, and this would enable underwriters to devote more attention to aspects of their work that depend on human expertise. I read how AI will bring improved efficiency to the paperwork involved with medicine; however, I remain guarded because it seems to also present higher risks related to data security.
Risk Management: Jennifer Freeden
Seeing the wave of AI continue to affect the healthcare industry, the Risk Management team just launched a webinar in December 2023 to cover the topic. We are at a place where there are more questions than answers, but AI is not going away. I am just starting to dabble with AI in my own work, mostly to help summarize meetings. However, our insureds are faced with more questions than ever about “if,” “how,” and “when” to implement AI into healthcare practices, and how best to use it if it is already integrated. It is vital that they understand the benefits and risks of utilizing AI and consider what is best for their patients and staff. AI is evolving each day, and we need to stay on top of the safety trends.
- Claims: Mike Severyn
- Underwriting: Debbie Farr
- Risk Management: Tina Santos
- Business Development: Doug Darnell
Claims: Mike Severyn
Currently neither I nor the Claims department use AI significantly in our day-to-day activities with our insureds and/or business partners. However, I do see this changing in the future. I do predict AI will have a significant impact on the MPL industry. I do see AI being used to assist or supplement the following claim activities: jury profiling, medical record tabbing or bookmarking, setting of reserves, and more.
In the future I do see AI dramatically impacting healthcare, which will impact the MPL industry as well. For example, I believe AI will be used to develop diagnoses and treatment plans for patients. I believe AI will be used to assist or replace healthcare providers in certain situations. Who will the patient sue then? The robot who provided the information, the developer who created the software, or the healthcare provider who relied on the information? Or all three?
Underwriting: Debbie Farr
When asked about my usage of AI, I initially thought, "I don't use AI." Upon reflection, I realized that I do. My most frequent interaction with AI is through Siri, whom I consult daily for spelling and informational queries. Recently I've also been introduced to ChatGPT, which has proven to be incredibly helpful in various tasks:
- Project Outlining: ChatGPT can generate outlines for projects, providing a structured framework that can then be filled in with details upon request.
- Writing Assistance: Whether it's drafting a letter or crafting a message, ChatGPT can refine and enhance the content to better suit my needs. It's capable of adjusting its suggestions based on my preferences.
- Reviews and Feedback: If I’m seeking alternatives or fresh perspectives, ChatGPT can assist in refining my comments or feedback, offering diverse language choices to avoid repetition.
ChatGPT serves as a versatile and reliable tool for enhancing productivity and communication. And yes, I used ChatGPT to refine this message!
Risk Management: Tina Santos
I have used ChatGPT on a very limited basis, mostly to enhance title creation and program descriptions for educational content. In the future I do see generative AI taking a more prominent role in Risk Management. As our insureds start utilizing different applications for medical record documentation, interpreting images, and even as clinical support, the risk of misinterpretation could escalate. Our department will have to explain the risks versus benefits of this technology. While AI does offer the advantage of providing analysis of complex scenarios and differential diagnoses clinicians may not be familiar with, there is no substitution for someone’s real world experience and education. Utilized as an enhancement in different contexts, AI has the potential to change and improve the healthcare landscape.
Business Development: Doug Darnell
I’m still writing my own reports. I see this as the next EMR, or cyber or privacy wave. There doesn’t seem to be any slowing of this advancement once it gets moving, and its widespread use seems to be a question of “when” rather than “if.” The important thing is to understand the limitations of generative AI before its widespread adoption and implementation into medicine. Those who move too quickly into this area may learn, like today’s school kids, that this isn’t the answer for every exam or problem. I think it will be important for ProAssurance to understand the varied uses of AI along the healthcare spectrum to be able to advise our clients of the myriad risks associated with its use. The benefits to doctor and patient alike are impossible to ignore; however, we must account for bumps in the road to progress.
- Risk Management: Mallory Earley
- Business Development: Seth Swanson
- Claims: Frank Bishop
- Underwriting: Christine Vaz
Risk Management: Mallory Earley
The Risk Management department does not utilize AI in our line of business yet, but there is potential in the future. Our insureds are already using AI in the form of scheduling software, summarizing clinical notes and medical records, and even using AI as a tool in diagnosis. Our department recently had a national webinar on Artificial Intelligence, and the main takeaways are to ensure understanding of its role and the implications of utilizing such advances while weighing the risks, benefits, and alternatives.
Although the buzz is around AI, the use of technology and tools is not new to the medical industry. This advancement in particular is another area to understand and validate prior to implementation while also recognizing its limitations. We do not anticipate AI assuming the role of risk manager or provider any time soon, but the advances could improve services and timeliness.
Business Development: Seth Swanson
AI can potentially impact malpractice insurance for doctors by enhancing diagnostics and reducing errors, leading to improved patient outcomes. However, as AI becomes more integrated into healthcare, legal and ethical considerations may arise, influencing insurance policies and premiums based on the evolving landscape of medical technology and its associated risks.
AI’s positive impacts include assisting doctors in diagnostics, personalized treatment plans, and administrative tasks. It can analyze vast amounts of medical data, providing quick and accurate insights and ultimately improving decision-making. However, there are concerns about job displacement and, as previously mentioned, ethical considerations related to the use of AI in healthcare. Striking the right balance between AI assistance and human expertise is crucial for maximizing the benefits for doctors and patients alike.
Claims: Frank Bishop
AI presents fascinating possibilities for streamlining and enhancing medical liability claims work. It's still essential to navigate this space with caution and a keen understanding of both its potential and limitations. ProAssurance Claims management is currently reviewing different AI platforms for implementation into our Claims space. Some of the potential areas where AI can currently aid Claims include:
- Document organization and analysis: AI can sort through vast amounts of medical records and other relevant materials, identifying key information and flagging potential issues faster than manual review. It can also prepare medical chronologies.
- Predictive analytics: AI algorithms can analyze past cases and identify patterns to predict the likelihood of success, the settlement values, and areas of weakness in the opposing party's case.
- Causation analysis: AI can help assess the connection between a provider's actions and the patient's harm, providing valuable insights for case evaluation and settlement negotiations.
- Literature review and evidence gathering: AI can quickly identify and retrieve relevant expert reports, scientific studies, and other resources for use by expert witnesses.
- Data analysis and visualization: AI can analyze complex medical data and present it in clear, understandable formats for internal review committee presentations.
Even within this response, approximately 75% of it was generated by AI.
Underwriting: Christine Vaz
AI is a hot topic in Underwriting these days, with the most common discussion being, how do we—and can we—utilize AI in the underwriting process? As we have seen in many industries AI can be extremely useful when it comes to automation of processes and data gathering. These are two areas in which I see AI being utilized now at ProAssurance and which will continue to develop in the future to enhance the customer experience. The second uncertainty around AI and underwriting is, how do we cover a provider or facility that is utilizing AI in their operations? Like many things in underwriting, this is a gray area. There are current discussions around who, what, where, when, and how to cover this exposure. Each situation is unique, and the experiences of the providers/organizations differ. The reliance on the technology used to form a diagnosis varies among provider types. Technology is also changing regularly. As we perfect coverage and answer these questions, our insureds will need to understand their own usage and communicate that to their broker/carrier. This will help to ensure that they will be covered in the event of a future claim and incorporate proper risk management to mitigate the risks associated with AI.
- Claims: Mark Lightfoot
- Underwriting: Tim Pingel
- Risk Management: Michele Crum
Claims: Mark Lightfoot
We are not yet using AI in Claims. We are looking into some applications including, for example, medical chronologies. AI may be and probably already is being used in medical care, particularly in the diagnostic setting.
Underwriting: Tim Pingel
While we aren’t using AI currently, we are starting to use data analytics, culling through all the information we have to help us determine trends in specialties. This allows us to make better decisions when it comes to risk selection. As those tools are further developed, we will be able to automate parts of the underwriting process, which will help improve decision-making and the time it takes to make those decisions.
Risk Management: Michele Crum
In Risk Management we are being asked to provide educational information about AI and the risks those using AI need to know. The research and experiences used today become outdated quickly, so our team believes we need to update our work at least every six months due to the rapid growth in use.
- Claims: Gina Harris
- Underwriting: Lucy Sam
- Risk Management: Katie Theodorakis
- Business Development: Andrea Linder
Claims: Gina Harris
We know that computers can look at old radiology films and “find” masses that cannot be seen with the naked eye. We also have a good sense that computers can predict when something unseen might evolve into something sinister. How will AI impact the standard of care for medicine?
Underwriting: Lucy Sam
An item that I mentioned at the Leadership Elite event was the possibility of AI somehow reducing the number of burdensome administrative tasks for providers and ultimately improving morale (e.g., assisting with medical record documentation and other paperwork).
Regarding the radiology example, ideally the radiologist and AI work in tandem to avoid missing items.
Risk Management: Katie Theodorakis
We do not currently use AI in Risk Management on the West regional team. Our biggest challenge with AI is staying on top of what is out there so we can educate physicians. Our fourth quarter Risk Management national webinar was all about AI. Physicians are already asking for updated education because the environment is changing so fast. There is great potential in AI, but with the potential comes risks.
Business Development: Andrea Linder
At this point, I do not see a use for AI in Business Development. I’m sure there are sales applications out there using AI, but I’ve not seen or heard of any. Our process is unique because our customers (brokers) are not the end users.
Healthcare’s New Data Dynamics
The influence of artificial intelligence on the medical field will be significant and rapid. By 2030, it is estimated that the AI healthcare market will reach nearly $200 billion.1 With this breakthrough technology's swift advancement and adoption, lawmakers and courts must address a wide range of novel and challenging issues. At or near the top of this list are questions surrounding the use of patient data, specifically patient medical data.
Patient medical data is crucial for AI healthcare systems because it enables them to learn from diverse health records, improving their accuracy in diagnosing and treating patients. However, integrating this data into AI systems presents unique challenges and requires careful consideration of privacy laws. The recent case of Dinerstein v. Google, 73 F.4th 502 (7th Cir. 2023), highlights many of these associated complexities and provides a potential roadmap for other jurisdictions to follow.
As part of a research partnership, the University of Chicago Medical Center (UCMC) shared anonymized patient records with Google to facilitate the development of AI-driven predictive health models. A former UCMC patient sued both entities, alleging multiple legal violations, including breach of contract, invasion of privacy, and consumer protection breaches. The U.S. District Court for the Northern District of Illinois dismissed the case, finding that the patient failed to state a claim and thus did not have standing to sue.
On appeal, the Seventh Circuit affirmed the dismissal, holding that the patient had not suffered a tangible injury due to the disclosure of his medical records. In reaching this conclusion, the court noted that most patient identifiers had been removed from the medical records, which sufficiently anonymized the data provided to the AI system.
In examining the possibility of future harm, the court acknowledged the theoretical possibility of identifying the patient by correlating his medical data with geolocation information but deemed such identification unlikely. In rejecting this potential “future re-identification” argument, the court noted that the alleged risk of future re-identification was not sufficiently imminent and could neither support monetary damages nor injunctive relief.2
Dinerstein suggests that proper de-identification of medical records will be essential in reducing legal exposure when sharing patient data with AI systems. Conveniently, this approach aligns with the most well-known patient privacy law, the Health Insurance Portability and Accountability Act (HIPAA). Once data is de-identified according to HIPAA standards,3 it is no longer considered Protected Health Information (PHI) and is not subject to HIPAA's use and disclosure restrictions.
While Dinerstein provides welcome guidance on this emerging issue, it remains to be seen if other jurisdictions will adopt a similar approach regarding patient privacy claims involving AI. Until then, providers utilizing AI systems should consider the following risk management steps to reduce legal risks when using patient medical data in AI systems:
1. Implement Robust Data De-identification: Use rigorous methods to deidentify patient data before using it in AI systems.
2. Ensure HIPAA Compliance: Adhere strictly to HIPAA guidelines for handling and sharing patient data.
3. Obtain Patient Consent: Inform patients how their data will be used and obtain their consent.
4. Develop Clear Policies: Establish and enforce clear policies for data handling and usage in AI applications.
5. Perform Regular Audits and Assessments: Conduct regular audits of data use and AI algorithms to ensure compliance with legal and ethical standards.
6. Stay Informed about Legal Developments: Keep abreast of changes in laws and regulations related to patient data and AI.
Meet Phyllis: Eastern's AI-Powered Mailroom Associate
We all have aspects of our jobs that are routine, even tedious. If you could delegate the boring, manual parts of your day-to-day, would you? That’s exactly what Eastern Alliance, part of ProAssurance Group, has done in its mailroom.
Meet Phyllis. She is an AI-powered, digital team member that can think, read, and intuit just like a human. She understands how to interact with insurance documents, systems, and processes so well that she indexes more than 80% of Eastern’s Claims mail.
Roots Automation
Phyllis was named by two of Eastern’s long-time mailroom associates, Ellen Leiphart and Rose Muchmore, but the idea for her came from a company called Roots Automation. They created the Roots Autonomous Workforce Platform—the world’s first language-oriented platform that enables insurance-knowledge workers to create AI-powered “digital coworkers” using speech and text.
Eastern began looking at the platform in September 2022 and decided to “hire” one of these digital coworkers for its mailroom. After an extensive training period led primarily by Jennifer Zimmerman, Eastern’s Business Systems Manager, Phyllis went live on April 26, 2023.
How to Train Your Robot
Over the course of several months, Roots Automation worked with Zimmerman as she explained exactly how the mailroom associates did their job, step by step, indexing thousands upon thousands of emails—primarily vendor bills, correspondence, state forms, and medical reports. She narrated how all of them needed to be reviewed and indexed to the right document type and sent to the right person.
As Zimmerman painstakingly explained the work, Phyllis began to learn.
She came programmed with key capabilities needed to effectively manage the documents and systems commonly found in an insurance mailroom. She holds an extensive amount of insurance-specific data and process knowledge through Roots Automation’s proprietary InsurGPTTM AI model—a large language model (LLM) created specifically for insurance.
She is built with AI that is capable of reading screens, documents, forms, and data like a human. She can dynamically identify and interact with objects on a computer screen, such as buttons, icons, form fields, and field names.
Leveraging advanced Natural Language Processing (NLP) to collaborate and communicate with people around document exceptions, Phyllis is continually adapting and learning. She captures transactional and metadata through interactions with people. If she is not “confident” in her ability to process an item, she can send that item for “review,” where one of our human team members can handle it for her.
Phyllis undergoes monthly performance retraining, with the goal of increased confidence and ongoing improvement—meaning she gets smarter every month. Currently Phyllis is successfully processing more than 80% of the items she encounters. By December 2023 Phyllis had processed more than 64,000 items.
Advantages of Automation
The benefits of an AI-powered team member are many. Phyllis can automate repetitive tasks, improve processes and workflows, enable quicker decision making, reduce human error, and be available 24/7.
“Prior to Phyllis, the average turnaround time for Claims mail coming into the mailroom was always three days,” said Zimmerman. “Occasionally, around the holidays or if someone was on vacation, we may have pushed to four or five days. With Phyllis, we are at same day processing. The obvious benefit of a digital coworker is that she can process incredibly quickly and do it all the time. She never gets sick or takes a day off.
Most importantly though, she eliminates the mundane, manual part of the work. Our associates can now take on new tasks because they have more time.”
Phyllis may do the work of three people, but she doesn’t replace our valuable human team members. The concern about AI replacing humans is a real one. But according to Harry Talbert, Eastern’s Senior Vice President, Information Systems, we needn’t worry. “We had no staff reductions with Phyllis,” he said. “The idea is to automate inefficiencies and reallocate people to other aspects of their work where they can provide more value—value that only a real person can provide.”
AI-powered digital coworkers are designed to streamline processes, not replace jobs.
Will She Replicate?
Phyllis has received a glowing performance evaluation. Is it possible that a Phillip might join our team in the future? Talbert says it’s likely.
“I think we’ll continue to seek opportunities to utilize the platform across the company to improve efficiencies and maximize our resources,” he said. “We’re budgeting for future projects, and asking, what makes the most sense?”
Clearly digital team members can save real people time, but we don’t want our service levels to suffer. Utilizing machine intelligence is only smart if it improves our customer interactions and frees people up to perform the work that needs a human touch.
About Eastern
Since its inception in 1997, Eastern has been committed to creatively serving the specialty workers’ compensation insurance needs of a diverse population of businesses and organizations. Through its primary operating subsidiaries—Eastern Alliance, Eastern Re, and Inova Re—Eastern is a specialty underwriter of workers’ compensation insurance products with an unwavering focus on delivering innovative solutions and services to the specialty workers’ compensation market. Learn more at EasternAlliance.com.
Retention Campaign Update
Each year we prioritize our marketing efforts to acquire and retain customers by looking for ways to further develop relationships. One of our most popular strategies is the complimentary book we offer our insureds as a thank you for being a loyal customer. The December 2023 issue of ProVisions introduced our latest retention campaign offering—The Laws of Medicine: Field Notes from an Uncertain Science by Dr. Siddhartha Mukherjee.
2023 Campaign Results
The 2023 campaign has officially ended and featured the popular book Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, by Dr. Eric Topol. The book explored the role artificial intelligence will play in the future of medicine and how deep learning algorithms can further a physician’s ability to create custom treatment plans.
We are pleased with the campaign’s success, showing an overall response rate of nearly 14%, with additional replies expected.
To receive any of our complimentary books, email AskMarketing@ProAssurance.com letting us know your mailing address. We appreciate everything you do to place and retain business with ProAssurance. If you have any questions about the retention campaign, please reach out.
Learn More: AI in Medicine
Listen as Dr. Siddhartha Mukherjee, Pulitzer Prize winning author of The Emperor of All Maladies interviews Dr. Eric Topol about his book, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again.
In this TEDMED Talk, Greg Corrado discusses the enormous role that AI and machine learning will play in the future of health and medicine, and why doctors and other healthcare professionals must play a central role in that revolution. Corrado is co-founder of The Google Brain team and Principal Scientist on Google's AI Healthcare team and has spent the last decade at the forefront of the AI revolution. From distilling data insights to improving the decision-making process, Corrado sees a multitude of ways that AI and machine learning can help magnify the healing powers of doctors. In fact, he believes that doctors who embrace AI will “see their healing powers expand more than they have in 100 years.”
In this TEDx Talk, Dr. Kurt Zatloukal, professor of pathology at the Medical University of Graz, Austria, and head of the Diagnostic and Research Center for Molecular Biomedicine, makes the case for why medicine needs AI.
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Today's AI algorithms require tens of thousands of expensive medical images to detect a patient's disease. What if we could drastically reduce the amount of data needed to train an AI, making diagnoses low-cost and more effective? TED Fellow Pratik Shah is working on a clever system to do just that. Using an unorthodox AI approach, Shah has developed a technology that requires as few as 50 images to develop a working algorithm—and can even use photos taken on doctors’ cell phones to provide a diagnosis. In this TEDGlobal Talk, Shah shares how this new way to analyze medical information could lead to earlier detection of life-threatening illnesses and bring AI-assisted diagnosis to more healthcare settings worldwide.
AI in Healthcare: Examining the Matrix of Risk & Opportunities
A thorough understanding of artificial intelligence, machine learning, and deep learning is important as we examine the risks and opportunities of their utilization in healthcare. We will define these terms as we explore current and future uses of AI in healthcare. We will also help your clients to identify potential risks to patient safety that could arise as they incorporate AI into their practices. These risks could potentially lead to medical professional liability claims. We hope the risk management strategies provided help decrease liability risk and improve patient safety when AI is utilized.
Objective
This enduring educational activity will support your clients’ ability to:
- Understand the current and future uses of AI in healthcare.
- Identify patient safety issues and liability risks associated with incorporating AI into healthcare.
- Implement strategies to decrease liability risk and improve patient safety when utilizing AI in a practice.
Physicians interested in taking this seminar can sign in at ProAssurance.com. Select “Physician Online Seminars” from the “Seminars” menu to gain access to our CME course library.
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Staking Your Leadership Position in AI Medical Liability Protection
My brilliant and innovative friend Peter called one evening to discuss some sales and marketing strategies for his latest brainchild—an ingenious app he created to revolutionize dermatology. Drawing from his success in implementing artificial intelligence into telephone communications and airline scheduling software, Peter unveiled a cutting-edge screening tool to combat malignant skin cancers.
After talking to Peter, I phoned my cousin Jennifer, a practicing dermatologist, to get her thoughts about his creation. She dismissed it almost immediately. During residency one of her attending physicians opined that AI could never diagnose as accurately as a human. I countered with Peter's assertion that an experienced dermatologist may witness thousands of "data points" over time, but an AI database has millions. Jennifer responded, "That may be, but I'm steering clear of AI until the technology is proven and mainstream."
As an MPL insurance agent, your role is not to convince healthcare stakeholders of AI's benefits but to help them understand and effectively manage the risks. However, HCPs like my cousin Jennifer may dismiss the topic until AI technology is commonplace. Don't be deterred! Commit to a leadership position in AI medical liability protection starting now.
Awareness Never Comes Too Soon
Artificial intelligence is a hot topic, and its increasing presence in healthcare is undeniable. While some HCPs may shy away from implementation, keeping up with liability issues is essential.
Showcasing how analogous providers have embraced AI while managing the risks is an effective way to draw attention. Given that HCPs might not relate to technologies and protocols they don't use, drawing parallels with their past experiences, such as when they adopted new clinical protocols, surgical techniques, and medical technologies, reminds them that adoption is closer than it appears.
Engaging the AI Agnostics
When dealing with AI-agnostic individuals (like my cousin), the focus should shift to education. Establishing awareness about medical liability and artificial intelligence is crucial, even for healthcare professionals who may not currently utilize AI technologies in their practice. Physicians don't always know what they don't know, and agents who keep them informed about the subtle aspects of liability provide invaluable support and insights.
Most HCPs find case studies irresistible. Look for real-life examples illustrating the value of a comprehensive MPL policy that includes AI coverage. This gives a practical understanding of how coverage safeguards clinicians and healthcare entities in real clinical scenarios.
Position for Success as AI Evolves
Positioning ProAssurance, your agency, and yourself as thought leaders at the crossroads of healthcare, AI, and MPL insurance presents a chance to carve out a distinctive presence in the marketplace.
Start by continuously educating yourself about healthcare AI issues and related liability. This ensures you have the knowledge and fluency to discuss relevant topics as the technology integrates more deeply into patient care. Prospects and clients will recognize your expertise, fostering a sense of recognition and trust.
Highlighting ProAssurance's educational resources on artificial intelligence showcases the role of MPL insurance in mitigating AI-related risks. Combined with your personal insights about policy coverage and ProAssurance's risk assessment services, you'll portray yourself as an agent who covers all aspects of MPL liability.
Seizing the Opportunity
While AI introduces new levels of risk, it also presents an unparalleled opportunity for MPL insurance agents to stand out and lead in an industry undergoing transformative changes. By showcasing your expertise and ProAssurance's educational and risk management resources, you can position yourself as a trusted advisor ready to help HCPs navigate the complex landscape of AI risk in healthcare (even the resistant ones like my cousin Jennifer).
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Written by Mace Horoff of Medical Sales Performance. Mace Horoff is a representative of Sales Pilot. He helps sales teams and individual representatives who sell medical devices, pharmaceuticals, biotechnology, healthcare services, and other healthcare-related products to sell more and earn more by employing a specialized healthcare system. Have a topic you’d like to see covered? Email your suggestions to AskMarketing@ProAssurance.com. |
Having a Bit of Fun
Half the fun of the new AI trend is poking the publicly available tools to see what they can do. We’ve rounded up a few of our favorites.
Cleanup.pictures
Need to remove an ex from the family wedding photos? Wish there wasn’t a garbage can behind your son in your photo of his epic soccer victory? Or simply want to eliminate someone’s name badge to make a photo less identifiable? Say no more! Cleanup.pictures helps you delete unwanted items from photos with no Photoshop skills required.
https://cleanup.pictures/
Interior AI
Want to redecorate your living room, but have no idea where to start? Interior AI lets you try a variety of styles on a photo of your space. Just swap a few things around and send off to the decorator.
https://interiorai.com/
