Faisal Hoque's Blog, page 9

How AI is Changing Cancer Treatment

Unlocking new possibilities for precision medicine.Key Takeaways AI enhances early cancer detection and diagnostic accuracy, reducing false positives and negatives, and improving patient outcomes. Personalized treatment plans using AI analyze patient-specific data to optimize therapy, predicting responses to treatments like immunotherapy. AI-driven preventive care reduces emergency visits and costs, improving patient quality of life and healthcare system sustainability. AI accelerates drug discovery, reducing time and costs, but challenges include potential biases, overreliance on technology, and data privacy concerns. Balancing AI innovation with human expertise and ensuring equitable application are essential for transforming cancer care.

Cancer is a deeply personal subject for me. My world was shaken when my son was diagnosed with a rare form of the disease. I witnessed how complex and unpredictable the journey could be, from the difficulty of diagnosing to finding the right treatments. But I am also witnessing how innovation in medical technology playing a role in his treatment.

These days, I often find myself investigating any new forms of treatment that may be of value for patients like him. That’s just one driving force behind my enthusiasm for the growing use of AI in the development and efficacy of immunotherapy.

Today, artificial intelligence is providing those tools, transforming how we diagnose, treat, and manage cancer. AI’s potential to improve patient outcomes, tailor treatments, and reduce the burden on health care systems is immense. As someone who has witnessed the life-saving impact of medical innovation, I’m optimistic that AI can help many more families avoid the devastating uncertainty I once faced.

AI-powered diagnostics: A game changer in early detection

Accurate and early detection is often the key to successful cancer treatment. However, traditional diagnostic tools, including biopsies, mammograms, and imaging scans, have limitations. False negatives and positives remain a challenge, leading to delayed treatment or unnecessary procedures. AI is making major strides in addressing these gaps.

AI-powered diagnostic tools are designed to improve the accuracy of detecting abnormalities. For instance, algorithms trained on massive datasets of mammograms have achieved near-human or even superior accuracy in spotting early signs of breast cancer. Some studies have reported that AI systems can evaluate mammograms with 99% accuracy, a figure that can dramatically reduce misdiagnoses and improve early detection rates.

Consider the UK’s National Health Service (NHS), which is currently piloting the world’s largest AI trial for breast cancer detection, involving over 700,000 mammograms. This trial aims to compare AI’s efficiency with that of human radiologists and potentially pave the way for more cost-effective diagnostic protocols. By using AI, health care providers can process scans more quickly, identify high-risk cases, and prioritize patient care.

Early and accurate diagnosis has long-term financial implications. When cancer is caught early, treatment options are typically less aggressive and less expensive, reducing the burden on both patients and healthcare providers. Furthermore, AI’s ability to catch subtle signals in imaging data—something that human eyes may miss—offers a new level of precision in oncology care.

Personalized treatment plans: Moving beyond one-size-fits-all approaches

Cancer is a highly individualized disease. Two patients with the same type of cancer may respond to treatments in entirely different ways due to genetic differences, underlying health conditions, and other factors. The emergence of precision medicine has underscored the importance of creating tailored treatment plans, and AI is at the forefront of this effort.

AI algorithms can analyze vast amounts of patient-specific data, including genetic information, medical history, imaging scans, and previous treatment outcomes. By identifying patterns within this data, AI can help clinicians predict how a patient will respond to certain therapies. For example, some AI systems are being used to determine which cancer patients are most likely to benefit from immunotherapy, a promising but often unpredictable treatment option.

Immunotherapy works by harnessing the body’s immune system to fight cancer, but its effectiveness varies widely among patients. By applying AI to genomic and molecular data, oncologists can predict whether a specific patient’s immune system is likely to respond to the treatment. This prevents patients from undergoing expensive and potentially ineffective therapies, ultimately saving time and resources while improving outcomes.

AI also facilitates real-time adjustments to treatment plans. As new data becomes available—such as how a tumor is responding to initial treatment—AI systems can recommend modifications, ensuring that patients receive the most effective care at every stage of their cancer journey.

Cost savings through preventive care and proactive interventions

One of AI’s most promising contributions to oncology lies in its ability to predict and prevent adverse events before they escalate. AI systems can monitor patient health in real time, identifying patterns that may indicate a risk of complications or emergency care needs.

At the Center for Cancer and Blood Disorders in Texas, AI tools are being used to predict which patients are most likely to visit the emergency room within the next 30 days. By identifying at-risk patients early, health care providers can intervene with proactive measures, such as adjusting medications or scheduling follow-up visits. This approach has led to estimated cost savings of $3 million by reducing unnecessary hospital admissions and emergency room visits.

Preventive care not only benefits healthcare systems financially but also improve patients’ quality of life. Fewer emergency visits mean less disruption to patients’ daily lives, reduced stress, and lower out-of-pocket costs. This shift toward preventive care, powered by AI, is an essential step in making cancer treatment more sustainable and patient centric.

Drug discovery and development: Profound impact

Perhaps the most profound impact of AI in oncology lies in drug development. Traditional cancer drug development takes an average of 10-12 years and costs upward of $2 billion per successful drug. AI is dramatically accelerating this process.

Insilico Medicine recently demonstrated the potential of AI in drug discovery by developing a novel cancer drug candidate in just 18 months at a fraction of the traditional cost. The company’s AI system analyzed millions of potential molecules to identify promising candidates, then optimized them for efficacy and safety.

Challenges in implementing AI: Balancing innovation with practicality

Despite its many advantages, the integration of AI into cancer care is not without challenges. One major concern is the potential overreliance on technology at the expense of human oversight. Some experts caution that while AI can provide valuable insights, it is not a replacement for the expertise and judgment of oncologists.

For example, in the UK, experts have raised concerns about whether the NHS’s focus on technological solutions might lead to neglecting essential aspects of cancer care, such as timely referrals and personalized follow-ups. A balance must be struck between leveraging AI’s capabilities and ensuring that human clinicians remain actively involved in decision-making.

Another challenge lies in ensuring that AI algorithms are equitable and unbiased. Since AI systems learn from historical data, they may inadvertently perpetuate existing disparities in health care access and outcomes. For example, if an algorithm is trained primarily on data from affluent populations, it may not perform as effectively when applied to underserved or minority communities. Addressing this issue requires careful oversight and continuous evaluation to ensure that AI benefits all patients equally.

Finally, data privacy and security concerns must be addressed. Cancer patients’ medical records contain sensitive information, and any breach of this data could have serious consequences. Health care organizations must implement robust cybersecurity measures and adhere to strict data protection regulations to ensure patient trust.

The future of AI in oncology

AI’s potential in cancer treatment is immense, but its success will depend on how well we navigate its challenges. By combining AI’s data-driven precision with the compassion and expertise of human clinicians, we can achieve a new era of personalized, effective, and cost-efficient cancer care.

Looking ahead, continued investments in AI research and development are critical. Governments, private sector organizations, and research institutions must collaborate to create standardized protocols for AI use in oncology. These protocols should prioritize patient safety, equity, and ethical considerations while fostering innovation.

As AI systems become more advanced, they could help predict cancer risks before symptoms even appear, offering patients the chance to take preventive measures. Furthermore, AI’s role in drug discovery could lead to the development of more targeted and less toxic therapies, further improving patient outcomes.

Conclusion

AI is not a cure for cancer, but it is a powerful tool that can complement existing medical practices and improve outcomes for patients. By enhancing diagnostic accuracy, personalizing treatment plans, and reducing the costs associated with emergency care and ineffective treatments, AI is paving the way for a more efficient and patient-centered approach to oncology.

However, we must approach this technological revolution thoughtfully. Balancing innovation with practicality, addressing bias, and safeguarding patient data will be essential in ensuring that AI delivers on its promise of transforming cancer care for the better. The future of oncology is bright, and AI is lighting the path forward.

Original article @ Medical Economics. 

The post How AI is Changing Cancer Treatment appeared first on Faisal Hoque.

Don’t Confuse Consumer AI with Big Tech’s Enterprise Initiatives

AI “is going to be very pervasive,” author @faisal_hoque says when discussing the fundamentals of the technology, adding: “Responsible innovation and responsible utilization is first and foremost.” pic.twitter.com/hT0Jxbtodj

— Yahoo Finance (@YahooFinance) February 7, 2025

Big Tech companies are spending big on artificial intelligence (AI), with Amazon (AMZN) set to spend more than $100 billion in capital expenditures in 2025.

Faisal Hoque, author of Transcend: Unlocking Humanity in the Age of AI, joins Catalysts with Seana Smith to talk about Big Tech’s AI spending in the context of China’s DeepSeek.

Hoque says the market may be conflating consumer and enterprise applications of AI. “The larger business tech companies’ business models are enterprise; it’s not necessarily just consumer [products],” he explains. “When you look at tech like DeepSeek and the things that are coming out in the market, the enterprises are not going to adopt those kinds of technology and this whole kind of sort of risk associated with it.”

“I’m not surprised at all that Amazon or Microsoft (MSFT) or any other Big Tech are spending more money to gear up their infrastructure and their models so that they can be utilized in a secure environment in an enterprise setting.”

Original article @ Yahoo Finance. 

The post Don’t Confuse Consumer AI with Big Tech’s Enterprise Initiatives appeared first on Faisal Hoque.

How to Identify the Right AI Partner for Your Organization

How do you know what kind of human/AI partnership is best for your company? Our expert offers his insight.

Nothing in life happens without partnerships. Something as simple as drinking a cup of coffee requires the collaborative efforts of hundreds if not thousands of people to bring about.AI is no different — harnessing its potential will require partnering internally and externally, across many traditional boundaries and silos. Indeed, partnership plays a particularly crucial role when working with AI because, given the many uncertainties we face, it is a kind of willful blindness to think that any single person or team will have all the answers.To respond effectively to this uncertainty requires leveraging group intelligence and widening our base of theoretical and practical expertise.3 Steps to Get Started on an AI Partnership Put strict frameworks in place around third-party AI partners. Decide which AI options make the most sense for you, and then thoroughly assess each one. Once you’ve chosen your AI, ensure you have solid human and technical support for your AI projects.Laying the GroundworkData-Minded PartnershipsFrom a certain perspective, working with AI is simply working with data. The twist is that AI can already analyze data in quantities and at speeds that are unimaginable for a human. This capability will only increase in the future, and it will eventually generate predictive models and decisions that will consistently exceed those we can arrive at without partnering with these non-human agents.But these outputs do not depend solely on the power of the algorithms that perform the analysis. If the data our AI agents process is inaccurate or untrustworthy, the solutions they provide will be equally flawed. When dealing with AI, we must, then, keep our “data auditor” hats on at all times to ensure that the results are helpful rather than harmful. As the computer science mantra states: Garbage in, Garbage Out.The same is true when we set out to build partnerships around AI. We must assess and reassess the data on which we make our strategic decisions around AI to ensure that the outcomes of our initiatives serve our organizational purpose. This can mean putting stringent frameworks in place to evaluate potential third-party partners or to assess the planning work carried out at different levels of the business.In a world in which the accuracy of data will only become more important, all businesses should be thinking about creating data probity processes overseen by either a senior manager or a company-wide data probity committee.Expand and Audit Your Knowledge BaseCreate an outline to determine what AI is right for you and your company based on purpose, existing knowledge base, cost, possible use cases and even viability. This crucial step provides an opportunity to consider the possibilities AI offers and to make a rapid initial assessment. Once you have established which options show the most promise, a more rigorous assessment of each will be needed.Start by identifying which of the elements you relied on in your outline planning were estimates, abstractions or simplifications. Then fill in these gaps with the necessary details. For instance, if you based staff needs and costings on numbers from a recent tech development project, you should now acquire accurate information on the specific skill sets you will need and the salaries you can expect to pay for them.Some businesses might already have teams or individuals they can tap for this detailed information. If that’s the case, you can put a process in place to turn that personal knowledge into institutional knowledge. In other cases, it may be necessary to hire specialists or to draw on third-party expertise to ensure that you can think about the components of your innovation portfolio from a fully informed perspective.Don’t forget that AI resources may themselves help in answering these questions (although, as always, make sure that any answers are properly sourced to avoid the dangers of hallucinations).Bridge the Capabilities GapStart by assessing the capabilities required for delivering each program and identify internal and external options for meeting those needs. In some cases, a business will already have considerable human and technical resources that can be used for the development of new AI projects.However, for companies embarking on their first major AI programs it may be necessary to put in place an aggressive training and/or hiring program to ensure that adequate staff are available.Alternatively, ask whether these capabilities can be acquired through third-party providers or by purchasing companies that already have the individuals and skills you will need. If you decide to use third-party service providers, ensure that you have robust systems in place for hiring and monitoring to ensure your needs are met on an ongoing basis.Interactive DesignConsult With StakeholdersAll implementations of AI will interact with humans, either directly or indirectly — this is in fact where much of AI’s most radical potential comes from. To ensure that these interactions are optimally beneficial, it is essential to keep the human experience in mind when developing AI agents.AI personas that communicate with an imperious tone or that fall into the “uncanny valley” between clearly non-human and convincingly human might generate responses ranging from annoyance to fear.Developing personas that are attuned to the needs of the humans they will work with is not just a matter of presentation but will also have a major impact on efficiency. AI agents should be designed to meet the specific needs of the humans who will be interacting with them. In some cases, that will mean optimizing for speed of interaction and efficient data communication. But in other cases, features such as conversational pauses and other elements of natural language use will be needed to create engaging interactions.Not all stakeholders will interact directly with the AI persona itself. Some will draw on data gathered second-hand, while others may have a regulatory or social interest in the way you implement AI in your business. As such, it is important to consult with representatives of government agencies and social groups that matter for the public standing of your brand.This will be particularly important in the early stages of AI implementation as humanity begins to develop its understanding of the place of AI in society and the guardrails that need to be placed around it.Concerns about tech-led job losses, for instance, are not a new phenomenon, but they come with a particularly sharp edge where AI is concerned due to the sweeping possibilities for social upheaval. Consulting on the speed and nature of your AI roll-out may be necessary not only to avoid public backlash against your business but also to help your company make morally grounded choices that do not create unnecessary harm.Choosing AI PartnersA critical question to ask at this stage is which human/AI partnership models will be most appropriate in which contexts. Answering this question will often take the form of deciding which AI personas to engage with and in what ways.For instance, a company might consider using a strategic planning AI persona in an advisor role at the senior leadership level, while seeking to replace some middle management functions with decision-making AI agents that can issue instructions to frontline staff.Image provided by Post Hill Press.However, collaboration is only one possible model for engagement. It is important to also consider whether other approaches might be fruitful. Most obviously, we should also consider whether competitive partnerships can add value to a business.For instance, an AI sales team built to implement current best practices could be set to compete with a human sales team to encourage the human team to develop innovative new approaches. Another useful model of engagement to consider is co-opetition (a portmanteau of “co-operation” and “competition”).The basic idea is to think of ways in which we can work with rivals to create value for all parties. An important strategy in this context is the idea of “working with … ‘complementors.’ A complementor is the opposite of a competitor. It’s someone who makes your products and services more, rather than less, valuable.”Excerpted from Chapter 6: OPEN for Business fromTranscend: Unlocking Humanity in the Age of AI (Post Hill Press; March 25, 2025).Original article @ builtin

The post How to Identify the Right AI Partner for Your Organization appeared first on Faisal Hoque.

DeepSeek AI and the Future of Tech Dominance

The real question isn’t just about market share, but national security and technological sovereignty. As China flexes its AI muscles, Silicon Valley faces its biggest challenge yet: innovate faster, or watch the AI crown slip away.

Is This the End of the Bull Market?

The emergence of DeepSeek AI has sparked intense debate about its potential impact on the U.S. tech sector and broader market dynamics. While disruptive technologies often trigger market rebalancing, ending a bull market typically requires broader economic catalysts like interest rate hikes, macroeconomic downturns, or systemic financial crises. DeepSeek AI alone likely won’t end the current bull run, but it could contribute to significant market volatility and potentially trigger a correction, especially if investors begin questioning the long-term dominance of U.S. tech giants.

Have a look at this USA Today article, “China’s DeepSeek AI sows doubts about US tech edge. Nasdaq, S&P 500 slide but Dow edges up“, from yesterday, where I commented on the market volatility.

Market Impact and Competitive Landscape

DeepSeek’s most striking innovation, the R1 open-source model, represents a significant shift in AI democratization. With performance reportedly comparable to proprietary models at 95% lower training costs, R1 enables smaller organizations and developers to access cutting-edge AI capabilities previously restricted to tech behemoths. This could fundamentally alter the competitive landscape for companies like NVIDIA, Google, and Microsoft, potentially affecting their market valuations and forcing strategic pivots to maintain their leadership positions.

The market’s response will largely depend on three key factors:

The actual performance and capabilities of DeepSeek’s AI models in real-world applications The strategic response of existing U.S. tech giants Broader economic conditions and investor sentimentU.S. National Security Questions

Drawing parallels with TikTok’s emergence, DeepSeek AI raises similar concerns about data privacy, national security, and economic competition. The platform could potentially collect vast amounts of data, raising questions about storage practices and potential access by foreign governments. If widely adopted, DeepSeek AI might create dependencies that pose cybersecurity risks and challenge U.S. technological leadership.

The open-source nature of R1 presents a double-edged sword. While community-driven transparency can accelerate innovation and vulnerability detection, it simultaneously provides malicious actors with easier pathways to analyze and potentially exploit system weaknesses. This accessibility could increase the attack surface for AI systems globally.

The success of DeepSeek R1 suggests that current U.S. export controls may inadvertently be accelerating Chinese innovation rather than containing it. As open-source AI models become integral to global infrastructure, there’s a risk of embedding different values and norms into these systems, potentially challenging Western technological standards and practices.

Evaluating Risk and Reward

When evaluating open-source models like DeepSeek R1, organizations can use frameworks such as OPEN and CARE, as defined in TRANSCEND, to identify opportunities and mitigate risks. The OPEN framework helps identify cost savings, transparency, and community innovation potential, while encouraging careful testing and clear governance. The CARE framework highlights critical security risks that need robust mitigation strategies.

The Path Forward

For U.S. tech companies to maintain their growth trajectory, they’ll need to demonstrate unprecedented adaptability and innovation. Success will require:

Flexible adaptation to new competitive pressures Continued focus on breakthrough innovations Responsible AI development practices Strong partnerships with security and regulatory bodies

Rather than viewing DeepSeek as a market-ending event, investors and tech companies should see it as a signal of ongoing technological disruption. The most successful players will be those who can quickly adapt, innovate, and leverage new technological capabilities while maintaining robust security measures.

To mitigate associated risks, policymakers and industry leaders must strike a delicate balance between fostering innovation and ensuring robust security measures. This includes promoting domestic open-source AI development and reassessing the effectiveness of existing export control policies.

The emergence of DeepSeek AI ultimately represents another chapter in the ongoing evolution of global tech competition.

While it may not end the bull market, it certainly signals the need for strategic repositioning and heightened attention to security concerns in the AI space.

Original article @ LinkedIN

The post DeepSeek AI and the Future of Tech Dominance appeared first on Faisal Hoque.

7 Critical Thinking Skills You Need in an AI Powered Workplace

​​AI is fundamentally altering how we think, reason, and relate to each other. Without strong critical thinking skills, we risk becoming passive consumers rather than active, thoughtful partners.

We’re at a fascinating yet concerning inflection point with AI. A recent Gallup poll reveals that 79% of Americans are already using AI-powered products in their daily lives, often without realizing it. Meanwhile, as MIT Sloan Review argues, the profound questions AI raises about consciousness, intelligence, and decision-making aren’t primarily technical problems—they’re philosophical ones. We need philosophy to help us understand what AI actually is, what it means to be intelligent, and how we should approach human-AI interaction. Without this philosophical foundation, we risk developing AI systems that don’t align with human values and ways of thinking.

This creates what I call a “philosophical emergency” in my forthcoming book TRANSCEND: Unlocking Humanity in the Age of AI.

Unlike previous technological revolutions that primarily changed what we could do, AI is fundamentally altering how we think, reason, and relate to each other. Without developing strong critical thinking skills specifically calibrated for this AI age, we risk becoming passive consumers of AI-driven decisions rather than active, thoughtful partners with this technology.

The stakes are incredibly high. It’s not just about using AI tools effectively—it’s about maintaining our capacity for independent thought, authentic human connection, and meaningful decision-making in a world where AI is increasingly embedded in every aspect of our lives. Here are seven essential critical thinking skills, grounded in philosophical wisdom, that we must develop to partner effectively with AI:

1. Recognizing limitations. (aka Epistemological Humility): Rooted in Socrates’ famous wisdom: “I know that I know nothing.” Also connects to Immanuel Kant’s limits of human knowledge and reason. When we recognize our own limitations, paradoxically, we become wiser in our interactions with AI.

Example: Deliberately choosing films outside AI’s recommendation bubble, asserting human creativity over algorithmic patterns.

 

2. Pattern Recognition vs Pattern Breaking: This draws from existentialist philosophy, particularly Sartre’s concept of radical freedom. While AI follows patterns, humans have what Sartre called the ability to “transcend the given”—to break free from predetermined patterns and create new possibilities.

Example: Choosing to have difficult conversations in person rather than using AI to craft perfect messages, prioritizing authentic connection over convenience.

 

3. Value-Based Reasoning: Connects to Aristotle’s concept of practical wisdom (phronesis)—the ability to discern what truly matters in any situation. Also relates to Max Scheler’s hierarchy of values, where he argues that some values (like love and spiritual growth) are inherently higher than others (like comfort and utility).

Example: Understanding that while an AI chatbot might offer comfort, it can’t replace the deep mutual understanding possible in human friendships.

 

4. Authentic Connection Awareness: Draws heavily from Martin Buber’s I and Thou philosophy. Buber distinguished between I-It relationships (treating others as objects) and I-Thou relationships (authentic encounters between subjects). This helps us understand the difference between AI interactions and genuine human connection.

Example: Regularly auditing which decisions you’ve unconsciously delegated to AI, from content choices to shopping decisions.

 

5. Freedom-Conscious Decision Making: Based on Hannah Arendt’s concept of “thoughtful willing”—making conscious choices rather than being carried along by automation and convenience. Also connects to Kierkegaard’s emphasis on authentic choice-making as central to human existence.

Example: Regularly auditing which decisions you’ve unconsciously delegated to AI, from content choices to shopping decisions.

 

6. Ethical Impact Analysis: Builds on Hans Jonas’s “imperative of responsibility”—the idea that modern technology requires a new kind of ethics that considers long-term and far-reaching consequences. Also incorporates utilitarian considerations about maximizing good outcomes while minimizing harm.

Example: Evaluating how using AI for hiring decisions might affect workplace diversity and human potential before implementation.

 

7. Transcendent Purpose Alignment: Draws from Viktor Frankl’s logotherapy and the human need for meaning, combined with Maslow’s concept of self-actualization. It’s about using AI while staying focused on higher human purposes and potential.

 

Example: Using AI to handle routine tasks while intentionally focusing freed-up time on meaningful work and relationships.

 

These seven critical thinking skills aren’t just nice-to-have philosophical concepts; they’re essential survival skills for maintaining our humanity and agency in an AI-augmented world. They help us engage with AI in a way that enhances rather than diminishes our humanity, allowing us to stay grounded in what makes us uniquely human while making the most of AI’s capabilities.

The philosophical foundations remind us that we’re not just dealing with technical challenges but with fundamental questions about human nature, purpose, and potential. The great philosophers have wrestled with these questions long before AI came along, and their insights provide rich frameworks for thinking about how we can partner with AI while maintaining and enhancing our humanity.

As AI continues to evolve and integrate more deeply into our lives, developing these critical thinking skills becomes not just important but essential for our individual and collective flourishing. They provide the mental tools we need to navigate this new territory thoughtfully and intentionally, ensuring that we remain active participants in shaping our AI-augmented future rather than passive recipients of whatever that future might bring.

Adapted/published with permission from ‘TRANSCEND’ by Faisal Hoque (Post Hill Press, March 25, 2025). Copyright 20204, Faisal Hoque, All rights reserved.

Original article @ Fast Company. 

[Source Illustration: Pixabay]

The post 7 Critical Thinking Skills You Need in an AI Powered Workplace appeared first on Faisal Hoque.

TRANSCEND: Readers’ Favorite Review

TRANSCEND presents an illuminating, practical perspective, equipping readers to tackle the challenges and opportunities of the AI era.

Reviewed by Carol Thompson for Readers’ Favorite

TRANSCEND: Unlocking Humanity in the Age of AI by Faisal Hoque is an exploration of the complex and evolving relationship between humans and artificial intelligence (AI). Hoque explores the philosophical and practical implications of coexisting with AI technologies that increasingly imitate and enhance human capabilities. The narrative is built on the premise that as AI becomes more integrated into our lives, we must adapt to these changes and actively participate in shaping the future trajectory of AI development. The book provides a balanced perspective—neither overly optimistic nor dystopian—on AI’s potential to enhance human life. It emphasizes the importance of using AI responsibly to elevate human potential without compromising the fundamental qualities that make us uniquely human.

Transcend presents a thoughtful exploration of the ethical issues associated with AI. Faisal Hoque invites readers to reflect on AI’s potential and implications for humanity in an increasingly technological world. This reflection encompasses our values, ethics, and trust in AI interactions. Hoque details frameworks that individuals and organizations can employ to maximize AI’s advantages while mitigating risks. These frameworks promote a proactive stance on AI, encouraging its use to address complex challenges and improve human connections rather than substituting them. Transcend presents an illuminating, practical perspective, equipping readers to tackle the challenges and opportunities of the AI era. Hoque’s work is a timely reminder that, despite AI’s continuous advancement, the future ultimately resides in human hands. Its impact on humanity now and in the future.

Original Review @ Reader’s Favorite. 

The post TRANSCEND: Readers’ Favorite Review appeared first on Faisal Hoque.

AI in 2025: Opportunities, Hype, and Reality

Success lies in understanding both the real potential andlimitations of Al.

AI in 2025 offers transformative opportunities in healthcare, business efficiency, and government services, but expectations must be managed. While AI won’t fully replace human functions or achieve perfect automation, it will significantly augment capabilities. Success requires balanced implementation using structured frameworks (such as OPEN and CARE) and maintaining human oversight of critical processes.

As artificial intelligence continues to evolve rapidly, understanding both its true potential and limitations becomes crucial for individuals, businesses, and governments. This article examines the realistic opportunities, potential hype, and frameworks for evaluation in the AI landscape of 2025.

Real Opportunities

The impact of AI will be felt across all sectors of society. For individuals, AI will fundamentally transform personal development through personalized healthcare systems, adaptive educational platforms, and enhanced career opportunities. This technology will reshape how people manage their daily lives and pursue their goals.

In the business sector, organizations will experience unprecedented gains in operational efficiency. AI-driven supply chain optimization, hyper-personalized customer experiences, and accelerated innovation processes will transform how companies create and deliver value to their stakeholders.

Governments will harness AI to revolutionize public service delivery. From developing data-driven policies to managing infrastructure more effectively, AI will enable more responsive and efficient governance at all levels of public administration.

Separating Hype from Reality

However, it’s crucial to recognize areas where AI expectations may exceed reality. For individuals, claims about AI completely replacing human capabilities in work, relationships, or achieving digital immortality will prove exaggerated. AI will serve as an augmentation tool rather than a replacement for human functions.

Organizations should be wary of promises about AI’s ability to autonomously run businesses and deliver dramatic cost savings. The reality will require significant human oversight, substantial investment, and ongoing maintenance.

In the government sector, claims about AI’s capacity to perfectly predict policy outcomes or fully automate public services will fall short. Complex social systems will continue to require human judgment and intervention for effective operation.

Frameworks for Evaluation

To navigate this landscape effectively, organizations can utilize two key frameworks: OPEN and CARE. The OPEN framework (Outline possibilities, Partner effectively, Experiment systematically, Navigate forward) provides a structured approach to evaluating and implementing AI opportunities.

The CARE framework (Catastrophize potential risks, Assess likelihood and impact, Regulate responses, Exit when needed) helps identify and manage potential risks and overhyped claims.

Underlying these frameworks is the “detach and devote” mindset – organizations must detach from unrealistic hype while devoting resources to proven, valuable applications that align with their strategic goals.

Success in the AI landscape of 2025 will depend not on chasing every trending possibility, but on maintaining a balanced approach that recognizes both the tremendous potential and practical limitations of AI technology. By using structured evaluation frameworks and maintaining realistic expectations, organizations can maximize the benefits while minimizing the risks of AI adoption.

Adapted from my book TRANSCEND.

Adapted/published with permission from ‘TRANSCEND’ by Faisal Hoque (Post Hill Press, March 25, 2025). Copyright 20204, Faisal Hoque, All rights reserved.

The post AI in 2025: Opportunities, Hype, and Reality appeared first on Faisal Hoque.

7 Leadership Practices for Thriving in 2025

As we prepare for 2025, leaders must embrace adaptability, purpose, and innovation to navigate rapid change.

Here’s how 4 I’s of transformational leadership—Idealized Influence, Inspirational Motivation, Intellectual Stimulation, and Individualized Consideration—can guide impactful leadership practices for the new year.

Why This Matters: The future demands leaders who are mindful, inclusive, and adaptable. By embodying the 4 I’s, we can create meaningful, sustainable change for 2025 and beyond

LinkedIn-Slide-7

The post 7 Leadership Practices for Thriving in 2025 appeared first on Faisal Hoque.

7 Innovation and Creativity Practices for 2025

As we step into 2025, creativity and innovation are no longer optional—they are essential for navigating an increasingly complex and interconnected world.

In Everything Connects, I explore how the greatest breakthroughs come from seeing relationships between people, ideas, and systems.

Creativity is the spark that transforms uncertainty into opportunity. It thrives when we embrace curiosity, diversity, and purpose. Innovation, its counterpart, is how we turn those sparks into meaningful impact, shaping solutions to the challenges of our time.

This year, as technological advancements accelerate and global issues demand bold action, our ability to connect and create will define how we lead and adapt. It’s about more than surviving change; it’s about shaping the future with intention, resilience, and vision.

LinkedIn-Slide-6-EC

The post 7 Innovation and Creativity Practices for 2025 appeared first on Faisal Hoque.

Life’s Humbling Journey

If we embrace it, age can teach us to confront fear with courage, face challenges with grace, discover love in loss, and grow stronger through empathy and an open heart.

As we grow older, life humbles us in ways we never anticipated. It’s in the quiet, unassuming moments that we’re forced to pause and reflect, revealing the essence of being human and the strength we didn’t know we had.

Loss becomes a more frequent companion with age, and it’s a profound teacher. The absence of a loved one, especially someone as central as a mother, creates a void that feels unbearable. Yet, within that void lies clarity. Love transcends time and presence. It lives on in memories, lessons, and the small, everyday gestures we once took for granted. Loss reminds us to treasure our connections and to find beauty in the ordinary moments that make up a life.

Life’s challenges often test us in ways we can’t prepare for. Watching our children or someone we love endure pain or illness strips away our illusions of control. These moments leave us raw but also teach us resilience. As we age, we come to understand that strength isn’t about fixing what’s broken but about showing up—being there with love and support, no matter how helpless we feel.

Adversity is a mirror, especially as the years pass. It reveals who we are when everything else is stripped away. It connects us to the shared struggles of humanity and reminds us of the hope that keeps us moving forward.

As Rumi said, “Try not to resist the changes that come your way. Instead, let life live through you. And do not worry that your life is turning upside down. How do you know that the side you are used to is better than the one to come?” The pain, the chaos, and the uncertainty all serve a purpose. They nurture growth and resilience, helping us bloom in ways we never imagined.

With age, we come to understand that life’s purpose isn’t in controlling every outcome but in learning to adapt and flow. The years teach us that perfection is a myth and that the real beauty lies in resilience—in finding strength during struggles and peace amid uncertainty. We discover that the measure of a meaningful life is not in the absence of hardship but in the grace with which we rise, again and again, to meet its challenges.

Copyright (c) 2024 by Faisal Hoque. All rights reserved.

The post Life’s Humbling Journey appeared first on Faisal Hoque.