Figure 1: Risk Types in Deep Application of Artificial Intelligence in the Financial Field (corresponding to 4.1). The purpose of this figure is to show the reader "what are the risks". Since these five dimensions are in a parallel or complementary relationship, it is recommended to use a "center-diffusion" or "multi-dimensional matrix" structure. 1. Drawing Logic Description Central Core: Labeled as "Risk Dimensions of Deep Financial AI Applications." Five Branches: Five bubbles or color blocks are drawn from the center, filled with: Risk of Decision-Making Autonomy (emphasizing the imbalance of human-machine relationship). Risk of Privacy Disclosure (emphasizing data security and individual rights). Social Bias and Discrimination (emphasizing the injustice of algorithms to specific groups). Risk of Attribution of Responsibility (emphasizing the ambiguity of law and morality). Market Fairness Risk (emphasizing the impact on the overall order of the financial market). Visual Enhancement: Under each category, Keywords can be added in small font to supplement specific manifestations, such as marking "sensitive data abuse, excessive power acquisition" under "privacy infringement." 2. Aesthetic Key Points Color Scheme: It is recommended to use "academic blue" or "business gray" as the main color, and the five branches can use gradient colors of the same color family (from dark to light), which appears rigorous and hierarchical. Iconization: Add a simple flat icon next to each title, such as: decision-making (brain or steering wheel), privacy (lock), bias (scales tilted). Symmetry: Ensure that the five branches are evenly distributed in space to avoid being top-heavy.
Chained Collaborative Learning Framework: A Collaborative Pr...
Chain-based Collaborative Learning Framework: A Collaborativ...
