 |
|
|
|||||
In 2024, Amazon introduced its AI-powered HR assistant, which helps managers with performance reviews and workforce planning. Similarly, Tesla deployed AI personas to assist in real-time production monitoring and supply chain optimization. These advancements showcase how AI personas are becoming essential in business operations, streamlining processes, and enhancing decision-making. As artificial intelligence evolves, we’re witnessing two interrelated phenomena shaping our future: AI personas and agentic AI. These developments bring both opportunities and challenges. Understanding AI Personas AI personas are collections of digital elements that combine to form hybrid characters with defined traits and priorities that interact with users in sophisticated ways. They range from professional advisors to creative collaborators and emotional support systems. Their ability to adapt interactions based on user needs makes them powerful tools for organizations. AI personas can be understood through three key dimensions: Function: The specific role and tasks the persona will perform Epistemic perspective: The knowledge base and information sources the persona draws upon Relationship type: The mode of interaction that best serves the intended purpose AI personas maintain consistent personality traits while evolving through interactions. For instance, an AI persona might serve as a strategic planning partner in a business context, accumulating knowledge about the organization’s goals and culture over time. The Emergence of Agentic AI Agentic AI refers to systems with increasing autonomy and decision-making capability. Unlike traditional AI that processes inputs and generates outputs, agentic AI can initiate actions and pursue objectives independently within defined parameters. The intersection of AI personas and agentic AI creates new collaboration possibilities. Consider these examples: Supply Chain Management: Tesla’s AI system doesn’t just process inventory datait autonomously adjusts production schedules, initiates parts orders, and redirects shipments based on real-time demand and disruption predictions. The system can decide to expedite certain components or switch suppliers without human intervention, though within predefined parameters. Financial Trading: Modern trading algorithms don’t simply execute preset rules. They actively monitor market conditions, news feeds, and social media sentiment, making independent decisions to open, adjust, or close positions. JPMorgan’s AI trading system, for instance, can autonomously modify its strategies based on changing market conditions. Network Security: Darktrace’s Enterprise Immune System doesn’t wait for security teams to identify threats. It learns normal network behavior and autonomously takes action to counter potential attacks, such as quarantining suspicious devices or blocking unusual data transfers. These systems showcase how AI can not only respond to requests but proactively identify opportunities, suggest improvements, and take initiative within defined parameters. Challenges and Considerations However, this evolution presents challenges: Authenticity and Trust: As AI personas become more sophisticated, maintaining transparency is critical. Organizations must establish clear guidelines on AI capabilities and limitations. Emotional Engagement: Humans naturally form emotional connections with AI personas, which can enhance interactions but also raise ethical concerns about dependency and manipulation. Autonomy Boundaries: Setting clear limits on what decisions AI personas can make independently versus requiring human oversight is essential. Managing the Future To harness these technologies effectively, organizations should focus on: Purposeful Design: AI personas should align with organizational goals, capabilities, and ethical guidelines. Human-Centered Approach: AI should enhance human capabilities rather than replace them. Ethical Frameworks: Transparency, privacy, and clear boundaries must guide AI interactions. Continuous Monitoring: Organizations should track AI behavior to ensure compliance and effectiveness. Implementation Frameworks The OPEN framework (Outline, Partner, Experiment, Navigate) provides a systematic four-step process for harnessing AI’s potential, guiding organizations from initial assessment through to sustained implementation. The CARE framework (Catastrophize, Assess, Regulate, Exit) offers a parallel structure for identifying and managing AI-related risks, that can guide organizations in implementing AI personas effectively: The OPEN framework helps organizations unlock AI’s potential through systematic: Outlining of possibilities and goals Partnership development with AI and stakeholders Experimentation with different approaches Navigation of evolving capabilities The CARE framework helps manage associated risks through: Catastrophizing to identify potential threats Assessment of risk likelihood and impact Regulation of risk through controls Exit strategies for when things go wrong Looking Forward The future of AI personas and agentic AI offers unprecedented potential for human cognition and collaboration. However, balancing technological advancement with ethical considerations is crucial. AI personas are reflections of human values and culture. Developing better AI personas isn’t just a technical challengeit’s a human one. Organizations must embody values that AI systems can learn and replicate. Success lies in embracing AI with “mature optimism”leveraging its potential while acknowledging limitations. The goal is to create AI personas that enhance human potential, support relationships, and help ndividuals become better versions of themselves. This transformation isn’t just about building better AIit’s about fostering a future where artificial and human intelligence thrive together in meaningful ways.
Category:
E-Commerce
A Texas pipeline company’s lawsuit accusing Greenpeace of defamation, disruptions, and attacks during protests against the Dakota Access Pipeline goes to trial in North Dakota on Monday, in a case the environmental advocacy organization says threatens free speech rights and its very future.The lawsuit stems from the protests in 2016 and 2017 over the oil pipeline’s planned Missouri River crossing, upstream from the Standing Rock Sioux Tribe’s reservation. The tribe has long argued that the pipeline threatens its water supply. Of the thousands of people who protested the project, hundreds were arrested.Energy Transfer and its subsidiary Dakota Access allege trespass, nuisance, defamation, and other offenses by Netherlands-based Greenpeace International and its American branch, Greenpeace USA. The lawsuit also names the group’s funding arm, Greenpeace Fund Inc.The jury trial in state court in Mandan, North Dakota, is scheduled to last five weeks. What are details of the case? Dallas-based Energy Transfer alleges Greenpeace tried to delay construction of the pipeline, defamed the companies behind it, and coordinated trespassing, vandalism, and violence by pipeline protesters. The lawsuit seeks millions of dollars in damages.The Dakota Access Pipeline was completed and has been transporting oil since June 2017.Greenpeace International said it shouldn’t be named in the lawsuit because it is distinct from the two U.S.-based Greenpeace entities, operates outside the U.S., and its employees were never in North Dakota or involved with the protests.Greenpeace USA said the plaintiffs have failed to back up their claims in the years since the protests.Earlier in February, a judge denied motions by Greenpeace to throw out or limit parts of the case. What is Greenpeace’s position? Representatives of the environmental organization founded over 50 years ago said the company just wants to silence oil industry critics.“This trial is a critical test of the future of the First Amendment, both freedom of speech and peaceful protest, under the Trump administration and beyond,” Greenpeace USA Interim Executive Director Sushma Raman told reporters. “A bad ruling in this case could put our rights and freedoms in jeopardy for all of us, whether we are journalists, protesters, or anyone who wants to engage in public debate.”Greenpeace USA helped support “nonviolent, direct-action training” on safety and de-escalation at the protests, Senior Legal Adviser Deepa Padmanabha said.Energy Transfer is arguing that “anyone engaged in a training at a protest should be held responsible for the actions of every person at that protest,” Padmanabha said. “So it’s pretty easy to see how, if successful, this kind of tactic could have a serious chilling effect on anyone who might consider participating in a protest.”Earlier in February, Greenpeace International filed an anti-intimidation suit in the District Court of Amsterdam against Energy Transfer, saying the company acted wrongfully and should pay costs and damages resulting from its “meritless” litigation. What does Energy Transfer say? An Energy Transfer spokesperson said the lawsuit is about Greenpeace not following the law.“It is not about free speech as they are trying to claim. We support the rights of all Americans to express their opinions and lawfully protest. However, when it is not done in accordance with our laws, we have a legal system to deal with that,” Energy Transfer spokeswoman Vicki Granado said in a statement.The company filed a similar case in federal court in 2017, which a judge dismissed in 2019. Soon after, Energy Transfer filed the state court lawsuit now headed to trial.Energy Transfer launched in 1996 with 20 employees and 200 miles (320 kilometers) of natural gas pipelines. Today the 11,000-employee company owns and operates over 125,000 miles (200,000 kilometers) of pipelines and related facilities. Jack Dura, Associated Press
Category:
E-Commerce
A year before Elon Musk helped start OpenAI in San Francisco, philanthropist and Microsoft cofounder Paul Allen already had established his own nonprofit artificial intelligence research laboratory in Seattle.Their mission was to advance AI for humanity’s benefit.More than a decade later, the Allen Institute for Artificial Intelligence, or Ai2, isn’t nearly as well-known as the ChatGPT maker but is still pursuing the “high-impact” AI sought by Allen, who died in 2018. One of its latest AI models, Tulu 3 405B, rivals OpenAI and China’s DeepSeek on several benchmarks. But unlike OpenAI, it says it’s developing AI systems that are “truly open” for others to build upon.The institute’s CEO Ali Farhadi has been running Ai2 since 2023 after a stint at Apple. He spoke with the Associated Press. The interview has been edited for length and clarity. Why is openness important to your mission? Our mission is to do AI innovation and AI breakthroughs to solve some of the biggest working problems facing humanity today. The biggest threat to AI innovation is the closed nature of the practice. We have been pushing very, very strongly towards openness. If you think about open-source software, the core essence was, “I should be able to understand what you did. I should be able to change it. I should be able to fork from it. I should be able to use part of it, half of it, all of it. And once I build my thing, I put it out there and you should be able to do the same.” What do you consider an open-source AI model? It is a really heated topic at the moment. To us, open-source means that you understand what you did. Open weights models (such as Meta’s) are great because people could just grab those weights and follow the rest, but they aren’t open source. Open source is when you actually have access to every part of the puzzle. Why aren’t more AI developers sharing training data for models they say are open? If I want to postulate, some of these training data have a little bit of questionable material in them. But also the training data for these models are the actual IP. The data is probably the most sacred part. Many think there’s a lot of value in it. In my opinion, rightfully so. Data plays a significant role in improving your model, changing the behavior of your model. It’s tedious, it’s challenging. Many companies spend a lot of dollars, a lot of investments, in that domain and they don’t like to share it. What are the AI applications you’re most excited about? As it matures, I think AI is getting ready to be taken seriously for crucial problem domains such as science discovery. A good part of some disciplines involves a complicated search for a solutionfor a gene structure, a cell structure, or specific configurations of elements. Many of those problems can be formulated computationally. There’s only so much you can do by just downloading a model from the web that was trained on text data and fine tuning it. Our hope is to empower scientists to be able to actually train their own model. Matt O’Brien, AP Technology Writer
Category:
E-Commerce
All news |
||||||||||||||||||
|
||||||||||||||||||