How does AI and robotics impact society?

An important element to keep in mind is that every technology we create is an extension of our own mental and/or physical abilities. As such, AI extends our brain-mind-consciousness to help us perform much better. Similarly robotics extend our physical abilities in various tasks. As such these technologies augment humans.

One of the important aspects of a synergy between AI and robotics is a technology maturity pf safety aspects,i.e. how the full technology stack (software, hardware, mechanics) of a robotic system can safely operate using AI

AI and robotics are more than technical terms; they represent a fusion of human ambition and technological advancement. While AI deals with the intellectual capabilities of machines, robotics emphasizes physical interactions. Together, they challenge the boundaries of what machines can accomplish. This synergy isn't just confined to labs and tech companies. It permeates daily life, redefining convenience, efficiency, and even creativity. However, it also raises profound questions about autonomy, ethics, and humanity's relationship with technology. A responsible engagement with AI and robotics demands not just technical proficiency but philosophical and ethical reflection.

It’s essential for both companies and governments to take the lead in retraining and upskilling workers whose jobs may be replaced by AI. AI doesn’t replace all jobs, but it will consolidate workforces in some areas. The good news? We have a great new way to upskill workers - AI! In particular, AI offers the ability to personalize education for learners in a way that was never possible before.

The digital era reverses all processes. In terms of office work, you do not commute to work; work comes to you online, anytime anyplace. Same applies to education; mass production era classrooms are obsolete, replaced by individualized learning online.

AI and robotics are indeed double-edged swords. On the one hand, automating mundane tasks, and on the other, rendering jobs obsolete. This dichotomy is not new. For example, the industrial revolution ushered in mechanization that led to massive labor displacement while spurring new industries and professions. Rather than resisting innovation, we must proactively address skill gaps and help people navigate the disruption. For example, we must revise educational curriculums to include relevant digital skills to prepare future generations. We must incentivize reskilling of the workforce, particularly folks whose jobs are most at risk of getting automated away. This needs both policy interventions and organizational planning.

AI will greatly impact marginalized groups. Particularly black girls and women of Gen Z. Bias is evident in the development of AI when diverse perspectives are not included. However, when included, AI has the ability to close achievement gaps in education and create innovation in the work place. We need to evaluate AI development and ensure groups of people are not be opted out.

AI's impact on work and education is transformative, especially in the field of wound care. By automating routine tasks, AI allows healthcare professionals to focus more on complex case management and personalized patient care. eKare's inSight, an AI-driven wound care solution, is a prime example of this transition. Concurrently, education is also being reshaped by AI, providing personalized and adaptive learning pathways, including teaching methods for using AI in healthcare. This prepares future healthcare professionals to utilize AI tools, like inSight, enhancing the quality and efficiency of wound care.

Example of AI applications in healthcare include: - Diagnosis of diseases such as cancer: by using AI image recognition to detect patterns and analyse CT scans - Drug discovery: by using AI to find new molecules or applying existing molecules for different diseases. For example, AI was used to identify optimal Rna sequences in Moderna Covid vaccine - Triage of patients and management of wards: using AI to predict which patient need urgent urgent care and how long patients need to stay at wards.

When we think of AI in health, we often envision surgical robots or disease predictions. However, there's a less obvious but equally significant impact - AI in mental health and emotional well-being. Consider the rise of AI-powered chatbots and virtual companions. These technologies are increasingly used to provide emotional support and mental health assistance. For instance, chatbots like Woebot or Paro have been developed to deliver cognitive behavioral therapy techniques to users, helping them manage symptoms of depression and anxiety.

Mostly along 3 pillars: - Predictions: AI models are able to diagnose diseases with performances that tend to be in line with doctors, and, more importantly, are able to predict the onset of a disease months or years in advance. This helps prevent diseases or estimate the progression so it can be slowed down. - Personalization: ML systems can identify the ideal procedures, treatments and interventions for a patient given their unique characteristics, opening up for personalization in medicine. - Paperwork: New tools such as ChatGPT and LLMs broadly are helping doctors by providing a simple interface through which they can enter text about the visit and let the AI translate that into ICD-10 (diagnosis) codes, CPT (procedure) codes, etc.

AI is significantly shaping the landscape of healthcare. It offers tools for preventive health, predictive diagnostics, and personalized treatment, leading to improved patient outcomes. AI algorithms can analyze large-scale health data to identify risk factors and suggest preventive measures. In the context of wound care, AI-based solutions can efficiently assess wounds and predict healing outcomes, enhancing the quality of care. Also, AI can improve patient wellbeing by providing telehealth services, enabling remote patient monitoring, and ensuring continuous care. This application is particularly crucial in managing chronic conditions, such as diabetic ulcers, where constant monitoring significantly improves health outcomes.

The marriage of AI and robotics in healthcare is an exciting frontier, offering potential for personalized and accessible care. From AI-powered diagnostics to robot-assisted surgeries, they promise a revolution in how healthcare is delivered. However, this is not a journey without pitfalls. There's a delicate balance between efficiency and empathy, precision and privacy. Ethical considerations must be front and center, ensuring that these tools are wielded with awareness of their limitations and potential biases. An algorithm should not only be seen as a problem-solver but as part of a complex human-centered system that values compassion as much as calculation.

We are already at a place where it’s difficult or impossible to distinguish real photographs from generated ones, or real human-written essays from generated ones. Transparent AI, also known as Explainable AI (xAI) will be key here. AI needs to be identified when used, and how the AI works should be explainable.

We must also consider the unintended consequences of fiction, in that fear of the unknown makes for great box office results--but also makes for a fearful population. AI is not the terminator, Skynet, etc. It can't read your mind. It does what humans do...in some ways more effectively but not on the whole. Entertainment's treatment of AI and robotics as villains is easy-they have no family or culture. But it does cause misinformation, anxiety, and fear of AI systems that is undue.

In entertainment and culture, AI and robotics are not just tools but mediums for expression. They enable new forms of creativity, making art and entertainment more interactive, immersive, and personalized. However, they also pose challenges to authenticity, diversity, and human connection. The ethical considerations extend to questions of copyright, representation, and even the nature of creativity itself. Engaging with AI and robotics in this context is an exploration of what it means to be human in a digitally mediated world. It's a dialog between technology and culture that continually shapes and is shaped by human values and aspirations.

At eKare, we understand the potential of AI in wound care extends beyond patient outcomes. It's about improving interaction between patients, clinicians, and technology. We focus on user-friendly interfaces and trust-building features, which integrate seamlessly into existing workflows. This user-centric approach aims to promote efficiency and enhance the overall wound care process.

It's worth noting that the impact of AI and robotics on society will likely be unevenly distributed, both among and within nations. Advanced economies with strong tech sectors may be able to harness these technologies more effectively than developing countries. Furthermore, within countries, access to and benefits from these technologies may be skewed toward certain demographic groups, potentially exacerbating existing social inequalities. Policymakers should strive to ensure that the benefits of AI and robotics are shared widely, and that no one is left behind in this technological revolution.

AI and robotics force us to adapt to a new reality of possibilities. Much like electricity, ships, computers, combustion engines, internet and so forth did.

Privacy and safety dilemmas are the cornerstones of unleashing AI powered systems to public in a large scale. For instance, AI powered robots sense a world around by means of optical sensors, whose output is governed by AI processing. Questions about the dataset creation (privacy), its completeness and coverage (safety) should be asked and replied properly

Given that AI is developed by humans and the data we feed into the models we need to be cognizant that we are often blind to our own biases, and the quality of data we provide as part of that training should be scrutinized. For example, if we train an AI to assess the creditworthiness of a loan applicant have we ensured that both the model’s logic and data do not introduce discriminatory racial or ethnic biases? While we may not intentionally do so, we could introduce historical training data which could cause such logic in the functioning of the model. An AI has no ethical or moral center, meaning it cannot question its own decisions or recommendations, so we will still require oversight from humans to guide its development and function.