![]() This TPB(EP) is designed to provide explanation of the general principles and matters that relate to the concept of fitness and propriety to be a registered tax agent, or BAS agent or tax (financial) adviser (collectively referred to as 'tax practitioners'). Last updated: 26 June 2017 Purpose of explanatory paper On 9 March 2017 the TPB updated this TPB(EP) to incorporate a reference to tax (financial) advisers, and to update the currency and accuracy of the TPB(EP). The TPB considered the submissions made and published the TPB(EP). The closing date for submissions was 6 June 2010. The TPB invited comments and submissions in relation to the information contained in it. The TPB released this TPB(EP) in the form of an exposure draft on 7 April 2010. The principles, explanations and examples in this paper do not constitute legal advice and do not create additional legal obligations beyond those that are contained in the TASA. This TPB(EP) is designed to assist tax practitioners, the relevant institutions, professional associations, potential registrants and the wider community to understand the factors that provide the basis for the TPB’s approach to the application of the TASA. ![]() It provides a detailed explanation of the TPB’s interpretation of the fitness and propriety requirements in the Tax Agent Services Act 2009 (TASA), translating these provisions into practical principles that can be applied by the profession. When I asked it to summarize the transcript of a meeting, it misunderstood a key piece of jargon, generating a muddled answer.This is a Tax Practitioners Board (TPB) Explanatory Paper (TPB(EP)).This TPB(EP) is intended as information only. Like real conversations, it can sometimes take a few questions to get the answer you want from Bard. This encourages the AI to produce an output that follows the same template. As a demonstration, I'll show Bard a step-by-step solution to the kind of thing I want to think through - which could be as simple as typing out a very basic dummy calculation and arranging it in a format I can understand. But it also lets you see the model's working, so you can follow along and pinpoint where dubious assumptions or mistakes have crept in. At the end of a prompt, add an extra line asking Bard to "think step-by-step," and it'll break down its solution into bite-size chunks.ĪI researchers have found this kind of communication increases the likelihood that AI systems will land on the correct answer. To make its thought process a touch more transparent, I use chain-of-thought prompting. ![]() When using the chatbot for problem-solving, such as calculating figures or setting up a schedule, I've found it makes basic errors in arithmetic by obscuring the assumptions used in its calculations. 'Think step-by-step'īard is a hardworking silent partner, which is a blessing and a curse: It will always produce an answer but won't ask for clarifications. Using references to track its statements like this is an easy way of keeping it on course. I've found that if Bard doesn't follow my instructions precisely, it tends to fabricate ideas. If one is missing, a quick re-prompt telling it to add in or make more explicit "fact X" usually does the trick. It lets me instantly check whether Bard has included every statement I gave it, just by me reading off the references. As a final instruction, I'll say: "When you use each fact in a sentence, label it by referencing its corresponding number." I'll tell it: "Base your answer on these following facts." Then, I'll type out a numbered list of statements. When I use Bard to draft an email, I usually want it to hit several key points. If I can't find any mention of them from a quick Google search, they're likely made up. That's why I get the model to do it for me.Īfter throwing it a question, I tell it: "Give me a list of the fundamental facts on which your response relied." It tends to generate a bullet-point rundown that, right off the bat, lets me check for self-consistency: Are all the listed facts reflected in the text, and are there any major statements that it's missed? From there, I can verify each individually.ĭepending on the complexity of my instructions, I've found it sometimes also returns the names of its sources. But it can take forever to pick out every implicit assumption or overt statement that needs verifying. I've found Bard is great for quickly generating answers to basic questions, how-to queries, and buying prompts. 'Give me a list of the fundamental facts on which your response relied' ![]() ![]() Sure, I still need to manually verify whatever Bard spits out, but these four prompts help me fact-check quickly, saving me time by making the artificial intelligence do the heavy lifting. It often indicates a user profile.īy using a few carefully honed prompts, I can identify and deal with any inaccuracies at a glance. Account icon An icon in the shape of a person's head and shoulders. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |