Tag: AI Integration

In the rapidly evolving landscape of artificial intelligence (AI), media companies and other businesses alike continue to find themselves entangled in a web of lawsuits and public criticism, shining a spotlight on the issue of ethical transparency. Journalism has long been plagued by issues around deception — consumers often wonder what’s sensationalism and what’s not. However, with the latest casualty in the ongoing Sports Illustrated debacle, whose reputation greatly suffered after being accused of employing non-existent authors for AI-generated articles, a new fear among consumers was unlocked. Can consumers trust even the most renowned organizations to leverage AI effectively?

To further illustrate AI’s negative implications, early last year Gannett faced similar scrutiny when its AI experiment took an unexpected turn. Previously, the newspaper chain used AI  to write high school sports dispatches, however, the technology proved to be more harmful than helpful after it made several major mistakes in articles. The newspaper laid off part of its workforce, which was likely in hopes AI could replace human workers.

Meaningful Change Starts at The Top

It’s clear the future of AI will face a negative outlook without meaningful change. This change begins at the corporate level where organizations play a key role in shaping ethical practices around AI usage and trickles down to the employees who leverage it. As with most facets of business, change begins at the top of the organization.

In the case of AI, companies must not only prioritize the responsible integration of AI but also foster a culture that values ethical considerations (AI and any other endeavor), accountability, and transparency. By committing to these principles, leadership, and C-level executives set the tone for a transformative shift that acknowledges both the positive and negative impact of AI technologies.

To avoid any potential mishaps, workforce training should be set in place and revisited at a regular cadence to empower employees with the knowledge and skills necessary to combat the ethical complexities of AI.

However, change doesn’t stop at leadership; it also relates to the employees who use AI tools. Employees should be equipped with the knowledge and skills necessary to navigate ethical considerations. This includes understanding the limitations and biases as well as learning from the mistakes of others who’ve experienced negative implications using AI technologies, such as the organizations previously aforementioned.

To Know More, Read Full Article @ https://ai-techpark.com/how-to-reconcile-lawsuits-and-public-backlash/

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Democratized Generative AI

The rapid advancement of artificial intelligence (AI) is revolutionising our lives and work, making processes more efficient. Technologies like large-scale machine learning and natural language processing models, such as ChatGPT, are pushing the boundaries of what was once confined to the realm of science fiction. However, a significant challenge remains in bridging the gap between technical brilliance and real-world application.

While AI has made significant progress in virtual environments, the introduction of AI-powered general-purpose robots in the physical world still faces substantial obstacles. Why is this the case, and how can we address these barriers? We explore the topic in more detail below.

Energy efficiency stands out as a primary obstacle. At its core, a robot is essentially a self-propelled computer. Anyone who has used a laptop knows that even the best devices struggle to operate for more than a few hours without recharging. With robots, energy demands are even higher due to internal processes and physical movement. Safety considerations prevent them from relying on tethered connections, necessitating extended battery life.

Unfortunately, current robot mechanics and autonomous systems lack the energy efficiency required for sustained operation. They require frequent and extended charging periods to perform optimally. While the first generation of robots is utilised in industrial settings for manufacturing, they remain constantly tethered to a power source. Although there are general-purpose robots available, like Sanctuary’s Phoenix humanoid, they are still cumbersome and expensive. It will likely take five to ten more iterations before we achieve a model that is truly independent, freely moving, and capable of performing various tasks.

To bridge this gap, we must start with smaller and simpler applications that gradually lead to full AI integration in the physical world. Cobots, which are robots designed for simple tasks, can play a crucial role in this process. Examples include self-driving wheelchairs, robots cleaning building facades, or autonomous technology performing complex, focused tasks like a smoke-diving robot searching for people or a drone fixing power lines. The key is focusing on single-duty performance, not only to enhance energy efficiency but also to achieve the highest standard of work.

Mechanical efficiency is another critical aspect. By improving the way robots move, potentially by utilising artificial muscles and joints to mimic human motion, we can reduce their energy requirements. However, achieving fully functional humanoid technology is still a considerable distance away.

To Know More, Read Full Article @ https://ai-techpark.com/overcoming-barriers-with-ai/ 

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