Category: Artificial Intelligence

By Jennifer Arnold, Engineer | Healthcare Startup Executive | Women’s Health Advocate

Women’s healthcare has long relied on standardized protocols, a disservice to the nuanced needs of female physiology. Women drive 80% of healthcare decisions, yet 59% feel their needs are unmet¹, revealing a market and clinical failure. Artificial intelligence (AI)—a probabilistic system that can learn from data and improve over time²—offers unprecedented potential to close this gap. But can these smart technologies truly deliver the personalized care women deserve?

How AI Makes Personalization Possible

AI’s power in women’s health lies in its ability to process vast, diverse data simultaneously. Modern neural networks—computational systems inspired by human brain connections—analyze hormonal patterns, genetics, symptoms, and behaviors, creating comprehensive models beyond traditional methods³. For endometriosis, where diagnosis averages 7-11 years⁴, AI systems show remarkable accuracy in early detection by finding subtle connections doctors might miss during brief appointments. Specifically, a study published in the Journal of Biomedical Informatics demonstrated that machine learning algorithms, when trained on patient-reported symptoms and medical history, could identify women at high risk for endometriosis with an accuracy of 89%⁵, helping reduce diagnostic delays. This means AI can sift through the complex web of symptoms, medical history, and even genetic predispositions to flag at-risk individuals potentially earlier than traditional methods.

What makes these systems particularly valuable is their ability to recognize patterns over time. Recurrent neural networks (RNNs), a specialized type of neural network, function like digital memory systems that remember past information, enabling them to track how female physiology changes through menstrual cycles, pregnancy, perimenopause, and beyond. Unlike standard neural networks that process each input independently, RNNs use feedback loops to give them a ‘memory’ of previous inputs, which is crucial for understanding sequential data³. Imagine an AI system that can analyze years’ worth of menstrual cycle data to predict hormonal imbalances or identify early signs of ovarian disorders. This addresses a fundamental limitation in traditional medicine: the tendency to take isolated snapshots rather than analyzing the dynamic, cyclical nature of women’s health.

Building on Limited Research Through Smart Computing

Historically, women were excluded from clinical trials, creating knowledge gaps. Before 1993, when FDA guidelines changed, women of childbearing age were routinely excluded from drug studies⁶—resulting in treatments optimized for male physiology. AI offers a revolutionary solution: extracting meaningful insights even when female participants are a fraction of study populations.

Through a technique called “data augmentation,” AI can artificially expand limited female datasets⁷. Imagine having data from only 100 women in a clinical trial of 1,000 participants. AI can analyze these 100 cases intensively, identifying subtle patterns and generating synthetic data points that represent similar women with slightly varied characteristics. This computational approach effectively “amplifies” the female voice in historical research without fabricating results. It is important to note that data augmentation is well-suited for predictive inference. However, these methods are not appropriate for determining the causal effect of the drug on a subpopulation of women. Data augmentation is best suited for prediction (what will happen) rather than causal analysis (why it will happen)⁸.

Similarly, “domain adaptation” algorithms can identify which insights from male-dominated studies might safely apply to women and which require female-specific recalibration. For example, an AI might recognize that a certain heart medication dosage needs adjustment for women due to physiological differences in metabolism and body weight⁹.

Modern AI performs post-hoc analysis on published studies, extracting female-specific data that may have been collected but never separately analyzed. For example, by reanalyzing historical medical records and tracking treatments and responses over time, AI can reveal insights about medication dosing, side effect profiles, and treatment efficacy for women that have been hidden. A study published in The Lancet in 2022 highlighted how retrospective analysis of cardiovascular trials revealed significant differences in drug response and adverse effects between men and women, insights that were previously overlooked due to aggregated data¹⁰. This computational archaeology reveals that many women have been consistently over-medicated or undertreated based on male-derived standards—problems AI can now help correct.

Ensuring Responsible Innovation

Despite its promise, AI in women’s health faces substantial challenges. Algorithmic bias remains pervasive—studies have shown that many healthcare algorithms underperform for racial and ethnic minorities due to biased training data. For example, A study revealed that AI tools used to diagnose asymptomatic bacterial vaginosis exhibited ethnic disparities¹¹. This is because AI models learn from the data they are trained on, and if that data reflects existing biases, the AI will perpetuate them. Addressing this requires diverse development teams and training data, alongside rigorous validation across demographic groups. 

Privacy concerns are equally critical given the sensitive nature of reproductive health data. Advanced protection techniques, such as differential privacy and federated learning, can safeguard individual information while preserving analytical insights¹².

The Path Forward

As the femtech sector expands toward a projected $43 billion by 2034¹³, AI stands poised to revolutionize women’s healthcare, offering a powerful tool to address systemic disparities. By leveraging AI’s capacity, we can uncover insights that have eluded traditional research methods, potentially saving millions of lives and billions in healthcare costs.

However, realizing this potential hinges on ethical implementation and inclusive design. As we stand at this technological crossroads, it is imperative that we approach AI development in women’s health with a focus on equity, transparency, and accountability. The power of AI to transform women’s healthcare is undeniable, but its impact—whether it narrows or widens health disparities—ultimately depends on how we choose to wield this powerful tool. By prioritizing diverse representation in AI development and rigorously addressing potential biases, we can ensure that this technological revolution truly serves all women, marking a new era of personalized, effective, and accessible healthcare.

References:

1. Lux Capital. (2025). Unlocking Potential: Artificial Intelligence for Women’s Health.
2. IBM. (2024). What is Artificial Intelligence (AI)?
3. Aledade. (2024). AI in Healthcare: Improving Patient Outcomes.
4. WomenTech Network. (2024). What Role Does AI Play in Advancing Women’s Health Initiatives?
5. Journal of Biomedical Informatics. (2023). Machine learning for early detection of endometriosis: A prospective study.
6. Harvard Business Review. (2024). How AI Could Help Reduce Inequities in Health Care.
7. Shorten, C., Khoshgoftaar, T.M. (2019). A survey on Image Data Augmentation for Deep Learning. Journal of Big Data 6, 60.
8. Pearl, J., Glymour, M., Jewell, N.P. (2016). Causal Inference in Statistics: A Primer. John Wiley & Sons.
9. Franconi, F., & Campesi, I. (2014). Sex and gender differences in pharmacology. British journal of pharmacology, 171(10), 2294–2308.
10. Lancet, The. (2022). Sex differences in cardiovascular disease. 399(10333), 1389-1400.
11. University of Florida. (2023, November 20). Study reveals bias in AI tools when diagnosing women’s health issue. ScienceDaily. 
12. OpenMined. (2024). What is Federated Learning?
13. GreenBook. (2024). The Femtech Frontier: Embracing AI for Women’s Health in 2024.

TechDogs, a leading technology platform, has recently joined forces with World Future Awards as one of their newest media partners. Renowned for delivering personalized, up-to-date tech content, TechDogs goes beyond being just a news source—it’s a comprehensive guide for professionals aiming to stay competitive in today’s fast-paced digital landscape. With a mission to empower individuals through insights across various sectors including leadership, finance, data science, and technology, TechDogs caters to a global audience across 67 countries, providing millions of readers with the knowledge and tools needed to advance their careers and succeed in business.

Artificial intelligence redefined creativity in 2024. Think about it: AI now handles 44% of creative industry duties, up from 25% three years ago. From $4.5 billion in 2020, the worldwide creative sector AI market is expected to reach $20 billion by 2025. Creative endeavors that took days or weeks are now done in hours thanks to AI tools.

AI-generated content is expected to make up 30% of digital material by year’s end, up from 10% in 2021. Over 60% of graphic designers utilize AI tools like DALL-E and Runway ML, and the music industry has experienced a 300% surge in AI-composed music for commercial use.

These statistics represent a major shift in creativity production, consumption, and value. AI is becoming a creative collaborator, expanding possibilities and redefining creativity.

AI – Creativity Era – Democratization of Creativity

With AI on the rise, we’re stepping into a new era of creativity. But here’s the thing—AI isn’t just a tool; it’s more like a creative partner. Recognizing how AI can enhance, augment, and reshape human creativity is crucial. When used right, AI can open up all sorts of new possibilities.

Some worry that AI might take over human creativity, but the reality is a bit different. Instead of replacing us, AI enhances our creativity. By taking care of the boring, repetitive tasks, AI gives us more time to dive into complex and abstract ideas. It’s like having a brainstorming buddy that offers fresh perspectives and helps refine concepts in ways we might not think of on our own.

One of the most exciting things about AI is how it’s making creativity more accessible to everyone. AI tools are becoming so easy to use that you don’t need formal training to create something amazing. Just as a few years back platforms like Canva and Grammarly empowered people to produce professional-quality work without breaking a sweat. AI Tools like ChatGPT, Adobe FireFly, Runaway, WriteSonic, DALL·E 3– are opening up the creative world to a much broader audience, making it more diverse and inclusive.

AI is revolutionizing marketing. Marketers can create blog posts, social media updates, and ad text in minutes using tools Jasper and Copy.ai. Picture a marketing team launching a new product. AI lets them swiftly develop content for different audiences, optimizing keywords and tone for optimum engagement. This saves time and improves marketing campaigns with less effort. Consider a startup that needs a brand makeover. They leverage AI-powered design tools like Looka and Designhill to produce brand-aligned logos, color schemes, and marketing materials without a large design team.

Opportunities Unleashed by AI

AI can be your creative assistant, confidant, and everything in between—if you want it to be. Think of it as a super-smart buddy who helps you brainstorm ideas, refine your work, and even tackle those pesky creative blocks. Here’s how AI is opening up new doors:

AI tools speed up creative processes. Imagine cutting down hours of work to just a few minutes! It’s like having a magic wand that helps you get things done faster. AI isn’t just a tool; it’s a partner in creativity. It lets us explore new styles and forms of art that we might not have considered before. Think of it as a new paintbrush for your creative canvas.

AI is a massive opportunity to drive more creativity in everything we do at work. But with this power comes questions about authenticity and originality. When AI creates something, who really owns it? Is it the person who programmed the AI, or is it the AI itself? This is a new area of research, and it’s sparking a lot of debates. We need to think about how to protect the originality of human creators while still embracing AI’s potential.

The Future of Creativity in an AI-Driven World

Looking ahead, collaborative creativity between humans and AI will become the norm. Imagine working side-by-side with an AI that can brainstorm ideas, suggest improvements, and even help execute creative projects. This partnership will allow us to push the boundaries of what’s possible, blending human intuition with machine precision.

As AI takes on more routine tasks, our roles in creative fields will evolve. We’ll focus more on nurturing creativity and imagination, while AI handles the grunt work. This shift will free us up to explore new ideas and innovate in ways we never thought possible.

AI will enable a level of personalized creativity that’s never been seen before. Imagine custom-tailored art, music, or literature designed specifically for you. This will make creative experiences more intimate and meaningful, as they resonate on a personal level.

The future of creativity isn’t about replacing humans with machines, but about creating a harmonious partnership where both can thrive.

By Vikramsinh Ghatge

Author Bio

Vikramsinh Ghatge is the Senior Director of Marketing at TechDogs, where he is responsible for leading the company’s marketing strategies, overseeing the development and execution of comprehensive marketing campaigns, and driving brand growth and engagement. With a keen focus on content marketing, digital marketing, and lead generation, Vikram ensures that TechDogs stays at the forefront of the technology publishing industry. He also collaborates closely with sales and product teams to align marketing efforts with business objectives and enhance customer experience.

 You can reach the author at vikram@techdogs.com, or www.linkedin.com/in/vikramghatge.

The following article by The European Financial Review is an insightful piece that illuminates the diverse effects of AI in the financial sector. It offers important perspectives on the opportunities and obstacles linked to AI adoption, highlighting the necessity for ethical considerations, strong data privacy protocols, and workforce adaptation strategies. As financial organizations increasingly adopt AI, maintaining transparency, fairness, and integrity will be essential in guiding this transformative process.

Artificial Intelligence (AI) stands out as a transformative force when it comes to Finance, revolutionizing traditional practices and driving innovation. Its integration into the financial services sector promises unprecedented efficiency, enhanced customer experiences, and robust risk management. However, as financial institutions embrace AI, thought-provoking insights emerge, shedding light on its multifaceted impacts and implications. 

Risk Management: AI’s Predictive Prowess  

With risk management, AI emerges as a game-changer, offering predictive insights and foresight capabilities by traditional methods. Through advanced algorithms and machine learning techniques, financial institutions can analyze vast datasets in real time, identifying patterns and anomalies with precision. This predictive prowess enables proactive risk mitigation strategies, enhancing resilience against market volatility and regulatory scrutiny. 

Customer Engagement: Personalization and Relationship Building  

AI’s integration empowers financial firms to deliver personalized experiences tailored to the unique needs and preferences of individual clients. Through advanced analytics and machine learning algorithms, institutions can offer customized recommendations, intuitive chatbots, and algorithmic trading platforms. These innovations not only streamline operations but also foster deeper client relationships, cultivating loyalty and trust. 

Ethical Considerations: Transparency and Accountability  

Despite its transformative potential, AI raises ethical considerations regarding transparency, bias, and accountability. The opacity of AI algorithms poses challenges in ensuring transparency and understanding the decision-making process. Moreover, biased algorithms risk perpetuating discriminatory practices, exacerbating social inequalities. As financial institutions deploy AI, it becomes imperative to establish robust governance frameworks that ensure ethical AI deployment and uphold principles of fairness and integrity. 

Data Privacy and Cybersecurity: Safeguarding Sensitive Information 

With access to vast troves of sensitive financial data, AI systems become prime targets for cyber-attacks and data breaches. The proliferation of AI exacerbates concerns surrounding data privacy and cybersecurity, threatening financial stability and eroding consumer trust. To mitigate these risks, financial institutions must implement stringent measures to safeguard data privacy and fortify cybersecurity defenses. 

Workforce Transformation: Reskilling and Upskilling Initiatives  

While AI-driven automation streamlines operations and augments productivity, it also prompts structural shifts within the workforce. Certain roles may become obsolete, necessitating reskilling and upskilling initiatives to equip employees with the requisite technical competencies. Moreover, AI fosters a culture of continuous learning and adaptability, prompting organizations to embrace workforce transformation initiatives. 

Regulatory Challenges: Balancing Innovation and Compliance  

The dynamic nature of AI poses challenges for policymakers and regulators, necessitating agile responses to balance innovation with risk mitigation. As financial institutions leverage AI to enhance operational efficiency and drive business growth, regulators must devise mechanisms to ensure compliance and mitigate systemic risks. Establishing clear regulatory frameworks is essential to foster responsible AI adoption and safeguard consumer interests. 

Fostering Responsible AI Adoption  

The integration of AI into the financial services sector holds immense promise for driving innovation and transformation. From risk management to customer engagement, AI empowers financial institutions to unlock new opportunities and deliver superior experiences. However, amidst the promises of technological advancement, it is crucial to address ethical, regulatory, and societal implications. By fostering responsible AI adoption and upholding principles of transparency, fairness, and integrity, we can navigate the AI frontier toward a future where innovation and ethics converge harmoniously. 

Please read more details at: https://www.europeanfinancialreview.com/navigating-the-ai-frontier-illuminating-insights-on-ais-impact-in-financial-services/

Welcome to an exclusive interview with Edward Frank Morris, newly appointed Board Member of the World Future Awards. Edward’s expertise spans the broad areas of marketing, generative artificial intelligence, and prompt engineering. During our conversation, Edward shared with us his insights on these and other equally exciting topics.

World Future Awards: Edward, congratulations on your appointment as a World Future Awards Board Member. Please tell us how your journey as a user of AI tools started and why you chose prompt engineering as one of the main areas of your professional activity.

Edward Frank Morris: Thank you so much! It’s an honor to be here with you, the other judges, and the candidates. I think it’s important for people to understand what Prompt Engineering is because it’s something we’ll all come across at some point. Prompt Engineering is very similar to communication, except this time, you’re giving those communications to an AI to do very specific things. Nearly every piece of Generative AI we have works in a Prompting-based fashion, and to be good at one area of prompting usually translates into other areas, providing the technology stands on its own. If you’re good at talking to machines, you’ll be good at AI. But if you’re great at talking to it, you’ll be ahead of the rest of the competition.

WFA: For many people, you have already become a guide to the expanding possibilities of artificial intelligence in content creation. But for those who are not yet using AI in business, what can you say about the key benefits that proper prompt engineering provides?

EFM: That’s a great question. I think most people don’t actually understand that the systems they get, whether it’s ChatGPT or similar, are massively underutilized without the correct coaching or upskilling. Most people have the incorrect assumption that how they use ChatGPT or other Large Language Models out of the box is good enough. But to get profound responses that are actually useful requires a lot of Prompt Engineering and creation. The right prompt can save you hours or days of time. The wrong prompt can cost you time. But using AI, generally, is always a net positive.

WFA: What achievements and milestones in your career have had the biggest impact on your expertise?

EFM: I think the biggest one so far has been the LinkedIn Top Voice award. The blue badge next to my name. I never tried to go for it, apply for it, or anything of the sort. I was new in my Prompt Engineering journey, and all I was doing was commenting on people’s posts, posting, and reaching out to other people to help them. Then, one day it just popped up. Validation from LinkedIn and the Microsoft team. A little whisper to tell me I was on the right path. As it would turn out, I was the first Prompt Engineering-specific person to get the award.

WFA: The scope of application of AI tools is extremely broad. What trends and areas of artificial intelligence use do you pay the most attention to in your work and why?

EFM: I think anything that completes tedious, repetitive tasks is worth attention. Don’t get me wrong, Generative AI isn’t 100% of the way there yet, but we are getting pretty close. It won’t be long until a lot of businesses find themselves in a situation where they wish they started adapting or at least considering AI now rather than later.

WFA: How do AI prompts differ from the usual search engine requests? What techniques or strategies help to form correct prompts and build communication to maximize the effectiveness of artificial intelligence?

EFM: I think that’s a good distinction to make. You can certainly use a lot of AI, even like ChatGPT, as a search engine. Asking it for answers to fairly difficult questions that Google or similar would stumble on when asked. But AI Prompts differ from Search Engines almost entirely. Mainly because you can make AI do anything as mundane as drafting up an email, all the way to giving you a psychological evaluation based on the DSM-5. The limits are almost endless.

WFA: How accessible is prompt engineering to non-technical users? Is expertise in coding or other high-tech areas critical for working with AI tools?

EFM: It depends on how technical you want to get with it. For entry-level? Nope! As long as you’re good at stringing together sentences and giving commands? Then you’ll get a good response. On the far more technical side, you can use Prompting with an API from a Large Language Model like OpenAI’s ChatGPT to get very different responses based on other interactive features. That’s where automation starts taking place where, with a click of a button, you can create a workflow that harvests information and then outputs it into several different things in seconds or minutes. All while still using Generative AI.

WFA: You are the founder of Enigmatica. Tell us about the activities of your company and the most exciting projects it has been involved in.

EFM: What we do typically is behind privacy and NDAs. We understand that a lot of companies want their AI and what makes their AI tick to be private. Most prompts are written in a specific way that makes it specific to that company, which allows them to look into solutions such as copyrighting the prompt itself. But our work varies. The company and I have made prompts for medical professionals that help diagnose illnesses or figure out illnesses. It’s made things that cut down massively on legal drafting for law firms. All sorts really. If you’re a firm that is using a lot of hours and resources in repetitive tasks? It can likely be automated by AI. Even the content creation side of things.

WFA: Prompt engineering is one of the most innovative and dynamic fields today. What are the most inspiring changes and innovations you have seen in it recently in terms of prompt design and functionality? 

EFM: I think a lot of people see Prompt Engineering as something that is fairly rigid and programmatic, like coding. But actually, it’s not. There are rules to follow, just like any language, but the beauty of Prompt Engineering is that you’re using plain words to talk to a super intelligent AI that can do most written or analytical things. Now, that’s not to say that you can give an AI two sentences and it’ll build a website – even though you could – but, with the right wording, directives, and lengths, you absolutely could. And with the right amount of creativity, you can make something truly special. Which is why I started the Da Vinci framework and methodology in the first place. To show people the importance of thinking outside of the box.

WFA: How do you see the foreseeable future of prompt engineering? What new opportunities for interacting with AI will evolve, and what challenges might arise?

EFM: We’re on the cusp of getting AI Agents and Chief Artificial Intelligence Officers are becoming more and more important. Ethically implementing this type of AI truly matters. But to make matters a bit more interesting, CAIOs need to have an understanding of how Generative AI and Prompting as a whole work so that they know the ins and outs for their own company. Knowing how it works, how to use it, and all the rest is so important – not to mention that prompt engineering will be massively important if you want to talk from a Generative AI standpoint. Although, sure, the popular narrative is that “AI won’t need prompting in the future!”, I would argue the opposite. How else are you to talk to a machine if you don’t know how to talk? How are you supposed to whisper and control it if you don’t know how?

WFA: What are your objectives as a World Future Awards board member? What do you expect from the WFA nominees, and what advice can you give them?

EFM: My advice to them is to focus less on the technical and more on what you’re giving the customer and end user. Sometimes it’s the most creative and strangest combinations that work best. Think about AI a lot like you would cooking. Roast meat? Logically, you would add salt. Seasoning that is savory. But what truly changed things like ribs, roast pork, or chicken? Honey. Sweet things. So that the savory could sing. The same applies to AI. Do not focus in on coding and making it technically fantastic (although you certainly could), but instead focus in on what the end result is for the user.

To learn more about Edward Frank Morris, visit his LinkedIn profile.