Read the following passage carefully and select the most appropriate option to fill in each blank:

The integration of algorithmic decision-making into modern corporate governance has [1] a seismic shift in how companies manage risk. While proponents argue that automated systems eliminate human bias, critics maintain that these systems often [2] existing inequalities. The algorithms, trained on historical data, inevitably internalize the systemic biases [3] in that data. Consequently, reliance on automated tools can lead to [4] discriminatory practices under the guise of objective analysis. To [5] these risks, progressive boards are implementing robust algorithmic auditing protocols. However, these audits are not a [6]; they require continuous adaptation to keep pace with evolving software. Furthermore, there is a growing demand for transparency, with stakeholders insisting that proprietary algorithms should not remain a black box. This has sparked a debate over intellectual property versus public accountability, a tension that remains largely [7] in current regulatory frameworks. As governments scramble to draft guidelines, the corporate sector must navigate this regulatory [8] with caution. Companies that proactively adopt ethical frameworks will likely emerge as leaders, whereas those that treat compliance as a mere [9] exercise risk severe reputational damage. Ultimately, the successful merger of technology and governance depends not on blind faith in automation, but on [10] oversight.