Sentient AI A year spent in artificial

Transcript:Sentient AI A year spent in artificial:
Sentient AI A year spent in artificial intelligence is enough to make one believe in God. The WashU Team Lei Song - JD/MBA Candidate Operations Shashwat Anand - First Year MBA Sales Rufus Ayisi - First Year MBA Strategy & Finance Divyam Jain - First Year MBA Strategy & Consulting AI is primarily giving a machine a capacity to process large amounts of data, and then produce results. The unique advantage is that we teach the machine to look for inputs. This creates the perception that the machine is "thinking". In today's data rich world, the more we know about the needs of our stakeholders, the better we can support them. Knowing about your wife's favorite color can help me suggest a product which I know will have a higher chance of being bought. A business' appetite to know about its customer is limitless. This is a win-win situation, as a customer experiences higher customisation, and businesses enjoy loyalty. Background How It Works Complexity Overplayed Major Benefits of AI Automation, Hyper-personalization, and Risk reduction Efficiency and productivity gains Automate routine tasks, freeing up humans to focus on creative and strategic work About half of America’s workforce feels their company’s AI deployment is outpacing the accuracy and productivity of comparable human activity Minimize the costs associated with performing mundane, repeatable tasks Increase in computing power to simultaneously process volumes of data Leveraging user data on demographics, behavior, and preferences, to create custom recommendations, content, and interactions Providing customer what they want without them asking for it Predictive forms of AI to anticipate both how attacks will occur and what motivates them Implement real-time monitoring capabilities to alert businesses on issues, recommend action, and, in some cases, even initiate a response Enhanced customer experience Improved monitoring and oversight Challenges EMPLOYEES Lack of awareness and misconception about the impact of AI on their job Skill Shortage CUSTOMERS Customer Privacy Ethical justification Inaccurate data leading to biased outcomes for end customers STAKEHOLDERS Vulnerability to human attacks and errors Data issues Provision for unforeseen consequences of AI Surveillance and warfare Recommendations Standard practices - Setting up clear standards for AI model development and documentation Break down Silos - Common AI and data policies across stakeholders in data science, legal, and governance teams Independent reviews – Reviews and audits using independent standards set up by FTC to evaluate model fairness, transparency Governance Framework – Creating a