Here's how you can proactively ask your boss for feedback on your AI work.

The best way we can implement and ensure our boss to give us a feedback: Mention what are our Intentions Clearly: Ensure your boss understands why feedback is crucial for your development and how it aligns with team goals. Acknowledge Their Perspective: Recognize the demands on their time and demonstrate how your growth benefits the team. Showcase our past Improvements: Highlight how you’ve applied past feedback and the positive impact it’s had on your work and team outcomes.

To proactively seek feedback on your AI work, approach your boss with a clear and concise request. Start by highlighting the specific project or task you worked on and express your interest in improving your skills. Ask for detailed insights on what you did well and areas for improvement. Frame your request positively, showing your commitment to growth and excellence. For example, "I would appreciate your feedback on the recent AI project. Could you share what worked well and any suggestions for enhancement?" This approach demonstrates initiative and a willingness to learn.

?? "Engage in Smart Conversations" ?? Ensure you thoroughly review your AI project objectives, methodology, and outcomes before seeking feedback from your boss. ?? Understand the algorithms, data sets, and machine learning techniques used in your work to ask specific questions. ?? Anticipate areas of improvement to make the feedback session more productive and show your dedication to the project. Let's keep the discussion going on how proper preparation can lead to valuable feedback and growth in the AI field. Your insights are valuable! ??

To effectively communicate the value of your AI initiatives to your boss, focus on the tangible benefits and outcomes of your projects. Highlight specific examples where AI has driven improvements, such as increased efficiency, cost savings, or enhanced customer experiences. Provide data and metrics to support your claims and show how these initiatives align with the company's strategic goals.

I strongly advocate for thorough preparation before seeking feedback on your project. Understanding your project's objectives, methodologies, and outcomes not only helps you ask specific, informed questions but also demonstrates your commitment and deep engagement. This level of preparedness can significantly enhance the quality of the feedback session, allowing for more targeted advice and constructive critique. Anticipating potential areas of improvement ensures that the discussion is productive and focused on enhancing the project's success.

Timing always matters request feedback once you have completed all the aspects of your project and during a time when your boss is not overwhelmed with other tasks, preferably scheduling a meeting in advance. This ensures they can give you their full attention for a productive discussion.

Sometimes, delivering a key note to the boss, is like timing the stock market. You don’t. Sometimes, we have to go back to the past. Remember elevator pitches? AI is changing the world and the world is not enough. There are 2 ways bosses will make time to listen to your AI pitch - profit or fear. If you succeed in talking about your AI-enabled work, you WILL get your feedback.

? For instance, at BotOracle, we’ve found scheduling feedback sessions right after a project sprint works wonders. It ensures feedback is fresh and actionable. Avoiding peak times like quarter-end or major deadlines, and framing the feedback session as a dedicated meeting rather than a casual chat, shows respect for your boss’s time and can lead to more insightful and constructive feedback. Sources: Forbes: How to Time Your Feedback Request Harvard Business Review: Getting Feedback Timing Right www.BotOracle.com

- Observe your boss's schedule and identify times when they are less busy, avoiding high-pressure periods like end-of-quarter or major deadlines. - Choosing a calm period ensures your boss can provide thoughtful and thorough feedback.

One thing that has been useful for me is choosing the right time to ask for feedback. Scheduling a dedicated meeting when your boss is calm ensures their full attention and a productive discussion. For example, I prefer asking for feedback at the end of an important milestone or before a significant presentation to maximize the impact of their comments.

Establish a framework, set the right expectations, soon, it will become habitual so you don't have to ask. I use SWOT analysis, specify that I'm seeking ways to improve and no constructive criticism would be poorly received. Help them understand yourself, and they'll likely provide much more helpful feedback.

One thing I found helpful is the emphasis on specificity when requesting feedback. In my experience, asking for general comments often leads to vague responses. However, by pinpointing particular aspects of my AI projects—such as the efficiency of algorithms or the validity of data modeling—I receive more actionable advice. This approach not only enhances the quality of feedback but also drives tangible improvements in my work. Clear, targeted questions pave the way for more productive discussions and better outcomes, ensuring that every feedback session is a step toward excellence.

?? For example, at BotOracle, we focus on specific aspects like the efficiency of our machine learning models or the accuracy of our data pipelines when seeking feedback. This targeted approach allows for detailed, constructive input that directly enhances our performance. By narrowing down your questions to particular components of your AI project, you’ll receive actionable insights rather than vague suggestions. Sources: Harvard Business Review: The Secret to Giving Great Feedback Forbes: The Power of Asking Specific Questions for Better Feedback

Erm, yes. And I beg to have a slight variation of opinion. Most if not all the time, bosses will switch off when jargon creeps in. Unless the boss is a technocrat and really interested in the nuts and bolts of KNNs and CNNs. If he is, then he is neither naive or bayesed (sorry about the puns ;)). He will already know it. So. I would think focus on the results or deliverables.

For me, being specific in my feedback requests has always been effective. Identifying particular aspects of my AI project, such as the efficiency of algorithms or the validity of data modeling, has helped me obtain targeted advice. This not only enhances the quality of feedback but also improves the results of my work. By asking precise questions, I have received valuable insights and concrete suggestions for improvement.

One thing that I’ve found helpful when discussing AI outcomes with management or with clients is to lay out expectations early and clearly. Let them know AI is not the same as SaaS and results aren’t expected to be turnkey. So early criticism and feedback will be coming from the right place and will help with quicker iterations and new feedback loops.

1. Inicie a conversa com uma pergunta aberta: "O que te chamou aten??o nesse projeto? O que você acha que funcionou bem e o que poderíamos ter feito diferente?" Essa pergunta coloca o chefe em uma posi??o de análise, abrindo espa?o para um diálogo rico e genuíno. 2. Ou?a ativamente: Preste aten??o n?o só às palavras, mas também à linguagem corporal e ao tom de voz do seu chefe. Essa leitura atenta permitirá que você compreenda as nuances da crítica e responda de forma mais precisa. 3. Fa?a perguntas: "Você poderia me explicar melhor por que a decis?o X te pareceu problemática? Essa atitude demonstra interesse genuíno em aprender e aprimorar. 4. Responda com objetividade: Apresente suas justificativas, mas esteja aberto a novas perspectivas.

One thing I found helpful in approaching feedback sessions with an open mind is recognizing them as learning opportunities rather than personal critiques. In AI projects, feedback often involves complex technical issues and strategic decisions. Actively listening, taking notes, and seeking clarification have been crucial in my experience. This approach not only enhances understanding but also fosters a culture of continuous improvement. Embracing criticism with an open mind can transform challenges into valuable insights, driving both personal and project growth.

It is crucial to approach feedback sessions with an open mind. Considering criticism as a learning opportunity rather than a personal attack has benefited me greatly. Actively listening, taking notes, and asking for clarifications have helped me better understand the points raised. This fosters a culture of continuous improvement, which is essential in AI projects.

Proactively asking for feedback on your AI work involves embracing criticism constructively. Start by scheduling a meeting with your boss, ensuring a convenient time for an in-depth discussion. Clearly articulate your desire for feedback, emphasizing your commitment to growth and improvement. Present your work with specific questions about areas where you seek input, such as model performance, data handling, or implementation strategies. Listen actively to the feedback, acknowledging both positive comments and constructive criticism.

Incorporating feedback into your work is a crucial step for continuous improvement. When your boss suggests improvements or adjustments to your AI models or data analysis, diligently implementing these changes demonstrates your commitment to excellence. Proactively following up not only shows that you value their input but also underscores your dedication to personal and professional growth. Scheduling a follow-up meeting to discuss the impact of these changes can further enhance your development and the project’s success.

One thing I found particularly helpful in the advice is the emphasis on follow-up meetings after implementing feedback. In my experience, this step not only demonstrates that you value the feedback but also allows for a collaborative review of the changes made. For instance, when my team adjusted our AI models based on input from our leadership, we scheduled a subsequent meeting to evaluate the impact of these changes. This proactive approach not only strengthened our solutions but also built greater trust and alignment within the team. It's a crucial practice for continuous improvement and professional growth.

Create visibility into efforts incorporating feedback. Make the areas of feedback a priority for follow up and follow through. Aim for a quick win within the first week to keep the momentum going while feedback is fresh.

I try to document the progress and outcomes of the suggested improvements. This not only shows that you are committed, but it also serves as a useful reference for future discussions and projects.

The efforts you made to get feedback mean nothing if you aren't able to look back and reflect. When reflecting it is important to pinpoint where your skills are lacking and try to fill those gaps.

It's all about showing that you're eager to improve and learn from your experiences. When you take a moment to think about how things are going, you can spot areas where you might tweak your approach or skills. This kind of self-awareness helps when you're talking to your boss because it shows you're serious about getting better. Also, it sets the stage for more productive conversations about your career development and how you can excel in the world of AI.

Take time to reflect on the feedback and how it can help you grow. Assess which areas you need to develop further and set specific goals for improvement. Use the feedback as a roadmap to enhance your skills and performance in AI. Reflecting on and integrating feedback into your work fosters a growth mindset and can lead to significant professional development.

- After receiving feedback, take the time to carefully review and understand it. - Identify specific points related to your AI project and consider how the suggested changes align with your goals. - This analysis helps in recognizing patterns and areas needing improvement.

I strive to stay committed to continuous learning. Attending workshops and courses helps me stay up-to-date with the latest AI trends and ensure that my projects benefit from the most advanced methodologies.

Schedule a brief meeting with your boss, emphasizing your commitment to improving. Ask specific questions about your AI work's strengths and areas for growth. Express openness to constructive criticism to enhance performance and contribute effectively to team goals.

Show initiative by seeking AI performance feedback! Schedule a meeting to discuss your work. Express your desire to improve and learn from your boss's expertise. Mention specific projects or areas where you'd appreciate feedback. Highlight your commitment to growth and willingness to address any shortcomings. By taking this proactive approach, you demonstrate your dedication and gain valuable insights to propel your AI career forward.

Visualization was the key. Instead of diving deep into theoretical points, visualizing the work helped efficient/effective communication.